Bernhard Schölkopf

1055 papers A* 213A 60B 21C 5Misc 6Journal 552Unranked 179

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CLT-Forge: A Scalable Library for Cross-Layer Transcoders and Attribution Graphs. CoRR Florent Draye, Abir Harrasse, Vedant Palit, Tung-Yu Wu, Jiarui Liu, Punya Syon Pandey, Roderick Wu, Terry Jingchen Zhang, Zhijing Jin, Bernhard Schölkopf
2026	J	`jnl`	Computational Arbitrage in AI Model Markets. CoRR Ricardo Dominguez-Olmedo, Bernhard Schölkopf, Moritz Hardt
2026	J	`jnl`	Deriving Hyperparameter Scaling Laws via Modern Optimization Theory. CoRR Egor Shulgin, Dimitri von Rütte, Tianyue H. Zhang, Niccolò Ajroldi, Bernhard Schölkopf, Antonio Orvieto
2026	—	`conf`	How Robust Are Router-LLMs? Analysis of the Fragility of LLM Routing Capabilities. EACL (Volume 1: Long Papers) Aly M. Kassem, Bernhard Schölkopf, Zhijing Jin
2026	J	`jnl`	Hyperbolic Busemann Neural Networks. CoRR Ziheng Chen, Bernhard Schölkopf, Nicu Sebe
2026	J	`jnl`	Identifying Intervenable and Interpretable Features via Orthogonality Regularization. CoRR Moritz Miller, Florent Draye, Bernhard Schölkopf
2026	J	`jnl`	Latent Causal Diffusions for Single-Cell Perturbation Modeling. CoRR Lars Lorch, Jiaqi Zhang, Charlotte Bunne, Andreas Krause, Bernhard Schölkopf, Caroline Uhler
2026	J	`jnl`	LoRA and Privacy: When Random Projections Help (and When They Don't). CoRR Yaxi Hu, Johanna Düngler, Bernhard Schölkopf, Amartya Sanyal
2026	J	`jnl`	On the Emergence and Test-Time Use of Structural Information in Large Language Models. CoRR Michelle Chao Chen, Moritz Miller, Bernhard Schölkopf, Siyuan Guo
2026	J	`jnl`	Preserving Historical Truth: Detecting Historical Revisionism in Large Language Models. CoRR Francesco Ortu, Joeun Yook, Punya Syon Pandey, Keenan Samway, Bernhard Schölkopf, Alberto Cazzaniga, Rada Mihalcea, Zhijing Jin
2026	J	`jnl`	Rethinking Easy-to-Hard: Limits of Curriculum Learning in Post-Training for Deductive Reasoning. CoRR Maximilian Mordig, Andreas Opedal, Weiyang Liu, Bernhard Schölkopf
2026	J	`jnl`	Rigidity-Aware Geometric Pretraining for Protein Design and Conformational Ensembles. CoRR Zhanghan Ni, Yanjing Li, Zeju Qiu, Bernhard Schölkopf, Hongyu Guo, Weiyang Liu, Shengchao Liu
2026	J	`jnl`	Use What You Know: Causal Foundation Models with Partial Graphs. CoRR Arik Reuter, Anish Dhir, Cristiana Diaconu, Jake Robertson, Ole Ossen, Frank Hutter, Adrian Weller, Mark van der Wilk, Bernhard Schölkopf
2026	—	`conf`	When Do Language Models Endorse Limitations on Human Rights Principles? EACL (Findings) Keenan Samway, Miu Nicole Takagi, Rada Mihalcea, Bernhard Schölkopf, Ilias Chalkidis, Daniel Hershcovich, Zhijing Jin
2026	J	`jnl`	When Do Language Models Endorse Limitations on Human Rights Principles? CoRR Keenan Samway, Miu Nicole Takagi, Rada Mihalcea, Bernhard Schölkopf, Ilias Chalkidis, Daniel Hershcovich, Zhijing Jin
2025	J	`jnl`	A Critical Perspective on Finite Sample Conformal Prediction Theory in Medical Applications. CoRR Klaus-Rudolf Kladny, Bernhard Schölkopf, Lisa M. Koch, Christian F. Baumgartner, Michael Muehlebach
2025	A	`conf`	Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation. AISTATS Amartya Sanyal, Yaxi Hu, Yaodong Yu, Yian Ma, Yixin Wang, Bernhard Schölkopf
2025	J	`jnl`	Adaptable Cardiovascular Disease Risk Prediction from Heterogeneous Data using Large Language Models. CoRR Frederike Lübeck, Jonas Wildberger, Frederik Träuble, Maximilian Mordig, Sergios Gatidis, Andreas Krause, Bernhard Schölkopf
2025	—	`conf`	Algorithmic causal structure emerging through compression. CLeaR Wendong Liang, Simon Buchholz, Bernhard Schölkopf
2025	J	`jnl`	Algorithmic causal structure emerging through compression. CoRR Wendong Liang, Simon Buchholz, Bernhard Schölkopf
2025	J	`jnl`	Are LLMs Good Safety Agents or a Propaganda Engine? CoRR Neemesh Yadav, Francesco Ortu, Jiarui Liu, Joeun Yook, Bernhard Schölkopf, Rada Mihalcea, Alberto Cazzaniga, Zhijing Jin
2025	A*	`conf`	Are Language Models Consequentialist or Deontological Moral Reasoners? EMNLP Keenan Samway, Max Kleiman-Weiner, David Guzman Piedrahita, Rada Mihalcea, Bernhard Schölkopf, Zhijing Jin
2025	J	`jnl`	Are Language Models Consequentialist or Deontological Moral Reasoners? CoRR Keenan Samway, Max Kleiman-Weiner, David Guzman Piedrahita, Rada Mihalcea, Bernhard Schölkopf, Zhijing Jin
2025	J	`jnl`	Are Language Models Efficient Reasoners? A Perspective from Logic Programming. CoRR Andreas Opedal, Yanick Zengaffinen, Haruki Shirakami, Clemente Pasti, Mrinmaya Sachan, Abulhair Saparov, Ryan Cotterell, Bernhard Schölkopf
2025	J	`jnl`	Artificial intelligence for modelling infectious disease epidemics. Nat. Moritz U. G. Kraemer, Joseph L.-H. Tsui, Serina Chang, Spyros Lytras, Mark P. Khurana, Samantha Vanderslott, Sumali Bajaj, Neil Scheidwasser, Jacob Liam Curran-Sebastian, Elizaveta Semenova, Mengyan Zhang, H. Juliette T. Unwin, Oliver J. Watson, Cathal Mills, Abhishek Dasgupta, Luca Ferretti, Samuel V. Scarpino, Etien Koua, Oliver Morgan, Houriiyah Tegally, Ulrich Paquet, Loukas Moutsianas, Christophe Fraser, Neil M. Ferguson, Eric J. Topol, David A. Duchêne, Tanja Stadler, Patricia Kingori, Michael J. Parker, Francesca Dominici, Nigel Shadbolt, Marc A. Suchard, Oliver Ratmann, Seth R. Flaxman, Edward C. Holmes, Manuel Gomez-Rodriguez, Bernhard Schölkopf, Christl A. Donnelly, Oliver G. Pybus, Simon Cauchemez, Samir Bhatt
2025	A*	`conf`	Can Large Language Models Understand Symbolic Graphics Programs? ICLR Zeju Qiu, Weiyang Liu, Haiwen Feng, Zhen Liu, Tim Z. Xiao, Katherine M. Collins, Joshua B. Tenenbaum, Adrian Weller, Michael J. Black, Bernhard Schölkopf
2025	J	`jnl`	Can Theoretical Physics Research Benefit from Language Agents? CoRR Sirui Lu, Zhijing Jin, Terry Jingchen Zhang, Pavel Kos, J. Ignacio Cirac, Bernhard Schölkopf
2025	J	`jnl`	Causal vs. Anticausal merging of predictors. CoRR Sergio Hernan Garrido Mejia, Patrick Blöbaum, Bernhard Schölkopf, Dominik Janzing
2025	J	`jnl`	Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models. CoRR Ruta Binkyte, Ivaxi Sheth, Zhijing Jin, Mohammad Havaei, Bernhard Schölkopf, Mario Fritz
2025	J	`jnl`	Causality can systematically address the monsters under the bench(marks). CoRR Felix Leeb, Zhijing Jin, Bernhard Schölkopf
2025	A*	`conf`	Conformal Generative Modeling with Improved Sample Efficiency through Sequential Greedy Filtering. ICLR Klaus-Rudolf Kladny, Bernhard Schölkopf, Michael Muehlebach
2025	J	`jnl`	Corrupted by Reasoning: Reasoning Language Models Become Free-Riders in Public Goods Games. CoRR David Guzman Piedrahita, Yongjin Yang, Mrinmaya Sachan, Giorgia Ramponi, Bernhard Schölkopf, Zhijing Jin
2025	J	`jnl`	Counterfactual reasoning: an analysis of in-context emergence. CoRR Moritz Miller, Bernhard Schölkopf, Siyuan Guo
2025	J	`jnl`	Cultural Alien Sampler: Open-ended art generation balancing originality and coherence. CoRR Alejandro H. Artiles, Hiromu Yakura, Levin Brinkmann, Mar Canet Sola, Hassan Abu Alhaija, Ignacio Serna, Nasim Rahaman, Bernhard Schölkopf, Iyad Rahwan
2025	—	`conf`	DARS: Dynamic Action Re-Sampling to Enhance Coding Agent Performance by Adaptive Tree Traversal. ACL (1) Vaibhav Aggarwal, Ojasv Kamal, Abhinav Japesh, Zhijing Jin, Bernhard Schölkopf
2025	J	`jnl`	DARS: Dynamic Action Re-Sampling to Enhance Coding Agent Performance by Adaptive Tree Traversal. CoRR Vaibhav Aggarwal, Ojasv Kamal, Abhinav Japesh, Zhijing Jin, Bernhard Schölkopf
2025	J	`jnl`	Democratic or Authoritarian? Probing a New Dimension of Political Biases in Large Language Models. CoRR David Guzman Piedrahita, Irene Strauss, Bernhard Schölkopf, Rada Mihalcea, Zhijing Jin
2025	J	`jnl`	Dexterous Robotic Piano Playing at Scale. CoRR Le Chen, Yi Zhao, Jan Schneider, Quankai Gao, Simon Guist, Cheng Qian, Juho Kannala, Bernhard Schölkopf, Joni Pajarinen, Dieter Büchler
2025	J	`jnl`	Do-PFN: In-Context Learning for Causal Effect Estimation. CoRR Jake Robertson, Arik Reuter, Siyuan Guo, Noah Hollmann, Frank Hutter, Bernhard Schölkopf
2025	J	`jnl`	Flexible Gravitational-Wave Parameter Estimation with Transformers. CoRR Annalena Kofler, Maximilian Dax, Stephen R. Green, Jonas Wildberger, Nihar Gupte, Jakob H. Macke, Jonathan Gair, Alessandra Buonanno, Bernhard Schölkopf
2025	J	`jnl`	Flipping Against All Odds: Reducing LLM Coin Flip Bias via Verbalized Rejection Sampling. CoRR Tim Z. Xiao, Johannes Zenn, Zhen Liu, Weiyang Liu, Robert Bamler, Bernhard Schölkopf
2025	J	`jnl`	From Pixels to Components: Eigenvector Masking for Visual Representation Learning. CoRR Alice Bizeul, Thomas M. Sutter, Alain Ryser, Bernhard Schölkopf, Julius von Kügelgen, Julia E. Vogt
2025	A*	`conf`	Generalized Interpolating Discrete Diffusion. ICML Dimitri von Rütte, Janis Fluri, Yuhui Ding, Antonio Orvieto, Bernhard Schölkopf, Thomas Hofmann
2025	J	`jnl`	Generalized Interpolating Discrete Diffusion. CoRR Dimitri von Rütte, Janis Fluri, Yuhui Ding, Antonio Orvieto, Bernhard Schölkopf, Thomas Hofmann
2025	J	`jnl`	Generation is Required for Data-Efficient Perception. CoRR Jack Brady, Bernhard Schölkopf, Thomas Kipf, Simon Buchholz, Wieland Brendel
2025	A*	`conf`	Generative Intervention Models for Causal Perturbation Modeling. ICML Nora Schneider, Lars Lorch, Niki Kilbertus, Bernhard Schölkopf, Andreas Krause
2025	J	`jnl`	How Robust Are Router-LLMs? Analysis of the Fragility of LLM Routing Capabilities. CoRR Aly M. Kassem, Bernhard Schölkopf, Zhijing Jin
2025	A*	`conf`	Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning. ICLR Patrik Reizinger, Siyuan Guo, Ferenc Huszár, Bernhard Schölkopf, Wieland Brendel
2025	A*	`conf`	Improving Large Language Model Safety with Contrastive Representation Learning. EMNLP Samuel Simko, Mrinmaya Sachan, Bernhard Schölkopf, Zhijing Jin
2025	J	`jnl`	Improving Large Language Model Safety with Contrastive Representation Learning. CoRR Samuel Simko, Mrinmaya Sachan, Bernhard Schölkopf, Zhijing Jin
2025	J	`jnl`	In silico biological discovery with large perturbation models. Nat. Comput. Sci. Djordje Miladinovic, Tobias Höppe, Mathieu Chevalley, Andreas Georgiou, Lachlan Stuart, Arash Mehrjou, Marcus Bantscheff, Bernhard Schölkopf, Patrick Schwab
2025	J	`jnl`	In-silico biological discovery with large perturbation models. CoRR Djordje Miladinovic, Tobias Höppe, Mathieu Chevalley, Andreas Georgiou, Lachlan Stuart, Arash Mehrjou, Marcus Bantscheff, Bernhard Schölkopf, Patrick Schwab
2025	J	`jnl`	International AI Safety Report 2025: First Key Update: Capabilities and Risk Implications. CoRR Yoshua Bengio, Stephen Clare, Carina Prunkl, Shalaleh Rismani, Maksym Andriushchenko, Ben Bucknall, Philip Fox, Tiancheng Hu, Cameron Jones, Sam Manning, Nestor Maslej, Vasilios Mavroudis, Conor McGlynn, Malcolm Murray, Charlotte Stix, Lucia Velasco, Nicole Wheeler, Daniel Privitera, Sören Mindermann, Daron Acemoglu, Thomas G. Dietterich, Fredrik Heintz, Geoffrey E. Hinton, Nicholas R. Jennings, Susan Leavy, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Alavaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Yan-Ning Zhang, Leandro Aguirre, Olubunmi Ajala, Fahad Albalawi Noora AlMalek, Christian Busch, André C. P. L. F. de Carvalho, Jonathan Collas, Amandeep Gill, Ahmet Halit Hatip, Juha Heikkilä, Chris Johnson, Gill Jolly, Ziv Katzir, Mary Kerema, Hiroaki Kitano, Antonio Krüger, Aoife McLysaght, Oleksii Molchanovskyi, Andrea Monti, Kyoung Mu Lee, Mona Nemer, Nuria Oliver, Raquel Pezoa Rivera, Audrey Plonk, José Ramón López Portillo, Balaraman Ravindran, Hammam Riza, Crystal Rugege, Haroon Sheikh, Denise Wong, Yi Zeng, Liming Zhu
2025	J	`jnl`	International AI Safety Report 2025: Second Key Update: Technical Safeguards and Risk Management. CoRR Yoshua Bengio, Stephen Clare, Carina Prunkl, Maksym Andriushchenko, Ben Bucknall, Philip Fox, Nestor Maslej, Conor McGlynn, Malcolm Murray, Shalaleh Rismani, Stephen Casper, Jessica Newman, Daniel Privitera, Sören Mindermann, Daron Acemoglu, Thomas G. Dietterich, Fredrik Heintz, Geoffrey E. Hinton, Nick R. Jennings, Susan Leavy, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Alavaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Yanning Zhang, Leandro Aguirre, Olubunmi Ajala, Fahad Albalawi Noora AlMalek, Noora AlMalek, Christian Busch, André Carvalho, Jonathan Collas, Amandeep Gill, Ahmet Halit Hatip, Juha Heikkilä, Chris Johnson, Gill Jolly, Ziv Katzir, Mary Kerema, Hiroaki Kitano, Antonio Krüger, Aoife McLysaght, Oleksii Molchanovskyi, Andrea Monti, Kyoung Mu Lee, Mona Nemer, Nuria Oliver, Raquel Pezoa, Audrey Plonk, José Ramón López Portillo, Balaraman Ravindran, Hammam Riza, Crystal Rugege, Haroon Sheikh, Denise Wong, Yi Zeng, Liming Zhu
2025	J	`jnl`	International AI Safety Report. CoRR Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Philip Fox, Ben Garfinkel, Danielle Goldfarb, Hoda Heidari, Anson Ho, Sayash Kapoor, Leila Khalatbari, Shayne Longpre, Sam Manning, Vasilios Mavroudis, Mantas Mazeika, Julian Michael, Jessica Newman, Kwan Yee Ng, Chinasa T. Okolo, Inioluwa Deborah Raji, Girish Sastry, Elizabeth Seger, Theodora Skeadas, Tobin South, Emma Strubell, Florian Tramèr, Lucia Velasco, Nicole Wheeler, Daron Acemoglu, Olubayo Adekanmbi, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Fredrik Heintz, Geoffrey E. Hinton, Nick R. Jennings, Andreas Krause, Susan Leavy, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang, Fahad Albalawi, Marwan Alserkal, Olubunmi Ajala, Guillaume Avrin, Christian Busch, André Carlos Ponce de Leon Ferreira de Carvalho, Bronwyn Fox, Amandeep Singh Gill, Ahmet Halit Hatip, Juha Heikkilä, Gill Jolly, Ziv Katzir, Hiroaki Kitano, Antonio Krüger, Chris Johnson, Saif M. Khan, Kyoung Mu Lee, Dominic Vincent Ligot, Oleksii Molchanovskyi, Andrea Monti, Nusu Mwamanzi, Mona Nemer, Nuria Oliver, José Ramón López Portillo, Balaraman Ravindran, Raquel Pezoa Rivera, Hammam Riza, Crystal Rugege, Ciarán Seoighe, Jerry Sheehan, Haroon Sheikh, Denise Wong, Yi Zeng
2025	J	`jnl`	Is Single-View Mesh Reconstruction Ready for Robotics? CoRR Frederik Nolte, Bernhard Schölkopf, Ingmar Posner
2025	A*	`conf`	Language Model Alignment in Multilingual Trolley Problems. ICLR Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, Sydney Levine, Jiarui Liu, Fernando Gonzalez Adauto, Francesco Ortu, András Strausz, Mrinmaya Sachan, Rada Mihalcea, Yejin Choi, Bernhard Schölkopf
2025	A*	`conf`	Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models. ICML Armin Kekic, Sergio Hernan Garrido Mejia, Bernhard Schölkopf
2025	J	`jnl`	Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models. CoRR Armin Kekic, Sergio Hernan Garrido Mejia, Bernhard Schölkopf
2025	J	`jnl`	Learning Nonlinear Causal Reductions to Explain Reinforcement Learning Policies. CoRR Armin Kekic, Jan Schneider, Dieter Büchler, Bernhard Schölkopf, Michel Besserve
2025	A*	`conf`	MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs. ICLR Andreas Opedal, Haruki Shirakami, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan
2025	J	`jnl`	Multi-Armed Bandits and Quantum Channel Oracles. Quantum Simon Buchholz, Jonas M. Kübler, Bernhard Schölkopf
2025	J	`jnl`	Multi-megabase scale genome interpretation with genetic language models. CoRR Frederik Träuble, Lachlan Stuart, Andreas Georgiou, Pascal Notin, Arash Mehrjou, Ron Schwessinger, Mathieu Chevalley, Kim Branson, Bernhard Schölkopf, Cornelia van Duijn, Debora S. Marks, Patrick Schwab
2025	J	`jnl`	Natural Building Blocks for Structured World Models: Theory, Evidence, and Scaling. CoRR Lancelot Da Costa, Sanjeev Namjoshi, Mohammed Abbas Ansari, Bernhard Schölkopf
2025	J	`jnl`	Online Learning and Unlearning. CoRR Yaxi Hu, Bernhard Schölkopf, Amartya Sanyal
2025	A*	`conf`	Orthogonal Finetuning Made Scalable. EMNLP Zeju Qiu, Weiyang Liu, Adrian Weller, Bernhard Schölkopf
2025	J	`jnl`	Orthogonal Finetuning Made Scalable. CoRR Zeju Qiu, Weiyang Liu, Adrian Weller, Bernhard Schölkopf
2025	J	`jnl`	PENEX: AdaBoost-Inspired Neural Network Regularization. CoRR Klaus-Rudolf Kladny, Bernhard Schölkopf, Michael Muehlebach
2025	J	`jnl`	Physics of Learning: A Lagrangian perspective to different learning paradigms. CoRR Siyuan Guo, Bernhard Schölkopf
2025	A*	`conf`	Preference Elicitation for Offline Reinforcement Learning. ICLR Alizée Pace, Bernhard Schölkopf, Gunnar Rätsch, Giorgia Ramponi
2025	—	`conf`	Quriosity: Analyzing Human Questioning Behavior and Causal Inquiry through Curiosity-Driven Queries. IJCNLP-AACL (Findings) Roberto Ceraolo, Dmitrii Kharlapenko, Ahmad Khan, Amélie Reymond, Rada Mihalcea, Bernhard Schölkopf, Mrinmaya Sachan, Zhijing Jin
2025	J	`jnl`	Real-time inference for binary neutron star mergers using machine learning. Nat. Maximilian Dax, Stephen R. Green, Jonathan Gair, Nihar Gupte, Michael Pürrer, Vivien Raymond, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
2025	J	`jnl`	Reparameterized LLM Training via Orthogonal Equivalence Transformation. CoRR Zeju Qiu, Simon Buchholz, Tim Z. Xiao, Maximilian Dax, Bernhard Schölkopf, Weiyang Liu
2025	J	`jnl`	Riemannian Batch Normalization: A Gyro Approach. CoRR Ziheng Chen, Xiao-Jun Wu, Bernhard Schölkopf, Nicu Sebe
2025	J	`jnl`	Robustness of Nonlinear Representation Learning. CoRR Simon Buchholz, Bernhard Schölkopf
2025	J	`jnl`	Scaling Behavior of Discrete Diffusion Language Models. CoRR Dimitri von Rütte, Janis Fluri, Omead Pooladzandi, Bernhard Schölkopf, Thomas Hofmann, Antonio Orvieto
2025	J	`jnl`	Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning. CoRR Patrik Reizinger, Bálint Mucsányi, Siyuan Guo, Benjamin Eysenbach, Bernhard Schölkopf, Wieland Brendel
2025	J	`jnl`	Sparse Attention Post-Training for Mechanistic Interpretability. CoRR Florent Draye, Anson Lei, Ingmar Posner, Bernhard Schölkopf
2025	A*	`conf`	Standardizing Structural Causal Models. ICLR Weronika Ormaniec, Scott Sussex, Lars Lorch, Bernhard Schölkopf, Andreas Krause
2025	J	`jnl`	TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models. CoRR Léo Grinsztajn, Klemens Flöge, Oscar Key, Felix Birkel, Philipp Jund, Brendan Roof, Benjamin Jäger, Dominik Safaric, Simone Alessi, Adrian Hayler, Mihir Manium, Rosen Yu, Felix Jablonski, Shi Bin Hoo, Anurag Garg, Jake Robertson, Magnus Bühler, Vladyslav Moroshan, Lennart Purucker, Clara Cornu, Lilly Charlotte Wehrhahn, Alessandro Bonetto, Bernhard Schölkopf, Sauraj Gambhir, Noah Hollmann, Frank Hutter
2025	A*	`conf`	The Directionality of Optimization Trajectories in Neural Networks. ICLR Sidak Pal Singh, Bobby He, Thomas Hofmann, Bernhard Schölkopf
2025	J	`jnl`	Towards Training One-Step Diffusion Models Without Distillation. CoRR Mingtian Zhang, Jiajun He, Wenlin Chen, Zijing Ou, José Miguel Hernández-Lobato, Bernhard Schölkopf, David Barber
2025	J	`jnl`	Tracing Multilingual Representations in LLMs with Cross-Layer Transcoders. CoRR Abir Harrasse, Florent Draye, Zhijing Jin, Bernhard Schölkopf
2025	J	`jnl`	Verbalized Machine Learning: Revisiting Machine Learning with Language Models. Trans. Mach. Learn. Res. Tim Z. Xiao, Robert Bamler, Bernhard Schölkopf, Weiyang Liu
2025	J	`jnl`	When Ethics and Payoffs Diverge: LLM Agents in Morally Charged Social Dilemmas. CoRR Steffen Backmann, David Guzman Piedrahita, Emanuel Tewolde, Rada Mihalcea, Bernhard Schölkopf, Zhijing Jin
2024	J	`jnl`	A Probabilistic Model behind Self- Supervised Learning. Trans. Mach. Learn. Res. Alice Bizeul, Bernhard Schölkopf, Carl Allen
2024	J	`jnl`	A Probabilistic Model to explain Self-Supervised Representation Learning. CoRR Alice Bizeul, Bernhard Schölkopf, Carl Allen
2024	—	`conf`	A diverse Multilingual News Headlines Dataset from around the World. NAACL (Short Papers) Felix Leeb, Bernhard Schölkopf
2024	J	`jnl`	A diverse Multilingual News Headlines Dataset from around the World. CoRR Felix Leeb, Bernhard Schölkopf
2024	J	`jnl`	Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation. CoRR Amartya Sanyal, Yaxi Hu, Yaodong Yu, Yian Ma, Yixin Wang, Bernhard Schölkopf
2024	J	`jnl`	Alien Recombination: Exploring Concept Blends Beyond Human Cognitive Availability in Visual Art. CoRR Alejandro Hernandez, Levin Brinkmann, Ignacio Serna, Nasim Rahaman, Hassan Abu Alhaija, Hiromu Yakura, Mar Canet Sola, Bernhard Schölkopf, Iyad Rahwan
2024	—	`conf`	Analyzing the Role of Semantic Representations in the Era of Large Language Models. NAACL-HLT Zhijing Jin, Yuen Chen, Fernando Gonzalez Adauto, Jiarui Liu, Jiayi Zhang, Julian Michael, Bernhard Schölkopf, Mona T. Diab
2024	J	`jnl`	Analyzing the Role of Semantic Representations in the Era of Large Language Models. CoRR Zhijing Jin, Yuen Chen, Fernando Gonzalez, Jiarui Liu, Jiayi Zhang, Julian Michael, Bernhard Schölkopf, Mona T. Diab
2024	A*	`conf`	Can Large Language Models Infer Causation from Correlation? ICLR Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona T. Diab, Bernhard Schölkopf
2024	J	`jnl`	Can Large Language Models Understand Symbolic Graphics Programs? CoRR Zeju Qiu, Weiyang Liu, Haiwen Feng, Zhen Liu, Tim Z. Xiao, Katherine M. Collins, Joshua B. Tenenbaum, Adrian Weller, Michael J. Black, Bernhard Schölkopf
2024	A	`conf`	Causal Modeling with Stationary Diffusions. AISTATS Lars Lorch, Andreas Krause, Bernhard Schölkopf
2024	J	`jnl`	Causal Responsibility Attribution for Human-AI Collaboration. CoRR Yahang Qi, Bernhard Schölkopf, Zhijing Jin
2024	A*	`conf`	Causal vs. Anticausal merging of predictors. NeurIPS Sergio Hernan Garrido Mejia, Patrick Blöbaum, Bernhard Schölkopf, Dominik Janzing
2024	—	`conf`	CausalCite: A Causal Formulation of Paper Citations. ACL (Findings) Ishan Kumar, Zhijing Jin, Ehsan Mokhtarian, Siyuan Guo, Yuen Chen, Negar Kiyavash, Mrinmaya Sachan, Bernhard Schölkopf
2024	J	`jnl`	CausalQuest: Collecting Natural Causal Questions for AI Agents. CoRR Roberto Ceraolo, Dmitrii Kharlapenko, Amélie Reymond, Rada Mihalcea, Mrinmaya Sachan, Bernhard Schölkopf, Zhijing Jin
2024	J	`jnl`	Compete and Compose: Learning Independent Mechanisms for Modular World Models. CoRR Anson Lei, Frederik Nolte, Bernhard Schölkopf, Ingmar Posner
2024	—	`conf`	Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals. ACL (1) Francesco Ortu, Zhijing Jin, Diego Doimo, Mrinmaya Sachan, Alberto Cazzaniga, Bernhard Schölkopf
2024	J	`jnl`	Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals. CoRR Francesco Ortu, Zhijing Jin, Diego Doimo, Mrinmaya Sachan, Alberto Cazzaniga, Bernhard Schölkopf
2024	J	`jnl`	Conformal Generative Modeling with Improved Sample Efficiency through Sequential Greedy Filtering. CoRR Klaus-Rudolf Kladny, Bernhard Schölkopf, Michael Muehlebach
2024	J	`jnl`	Cooperate or Collapse: Emergence of Sustainability Behaviors in a Society of LLM Agents. CoRR Giorgio Piatti, Zhijing Jin, Max Kleiman-Weiner, Bernhard Schölkopf, Mrinmaya Sachan, Rada Mihalcea
2024	A*	`conf`	Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents. NeurIPS Giorgio Piatti, Zhijing Jin, Max Kleiman-Weiner, Bernhard Schölkopf, Mrinmaya Sachan, Rada Mihalcea
2024	J	`jnl`	Deep Backtracking Counterfactuals for Causally Compliant Explanations. Trans. Mach. Learn. Res. Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach
2024	A*	`conf`	Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding. ICLR Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Rätsch, Guy Tennenholtz
2024	A*	`conf`	Detecting and Identifying Selection Structure in Sequential Data. ICML Yujia Zheng, Zeyu Tang, Yiwen Qiu, Bernhard Schölkopf, Kun Zhang
2024	J	`jnl`	Detecting and Identifying Selection Structure in Sequential Data. CoRR Yujia Zheng, Zeyu Tang, Yiwen Qiu, Bernhard Schölkopf, Kun Zhang
2024	—	`conf`	Diffusion-based learning of contact plans for agile locomotion. Humanoids Victor Dhédin, Adithya Kumar Chinnakkonda Ravi, Armand Jordana, Huaijiang Zhu, Avadesh Meduri, Ludovic Righetti, Bernhard Schölkopf, Majid Khadiv
2024	A*	`conf`	Do Finetti: On Causal Effects for Exchangeable Data. NeurIPS Siyuan Guo, Chi Zhang, Karthika Mohan, Ferenc Huszar, Bernhard Schölkopf
2024	J	`jnl`	Do Finetti: On Causal Effects for Exchangeable Data. CoRR Siyuan Guo, Chi Zhang, Karthika Mohan, Ferenc Huszár, Bernhard Schölkopf
2024	—	`conf`	Do LLMs Think Fast and Slow? A Causal Study on Sentiment Analysis. EMNLP (Findings) Zhiheng Lyu, Zhijing Jin, Fernando Gonzalez Adauto, Rada Mihalcea, Bernhard Schölkopf, Mrinmaya Sachan
2024	A*	`conf`	Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners? ICML Andreas Opedal, Alessandro Stolfo, Haruki Shirakami, Ying Jiao, Ryan Cotterell, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan
2024	J	`jnl`	Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners? CoRR Andreas Opedal, Alessandro Stolfo, Haruki Shirakami, Ying Jiao, Ryan Cotterell, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan
2024	J	`jnl`	Efficient Search and Learning for Agile Locomotion on Stepping Stones. CoRR Adithya Kumar Chinnakkonda Ravi, Victor Dhédin, Armand Jordana, Huaijiang Zhu, Avadesh Meduri, Ludovic Righetti, Bernhard Schölkopf, Majid Khadiv
2024	J	`jnl`	Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets Adaptive Noise Levels. CoRR Timothy D. Gebhard, Jonas Wildberger, Maximilian Dax, Annalena Kofler, Daniel Angerhausen, Sascha P. Quanz, Bernhard Schölkopf
2024	A*	`conf`	From Causal to Concept-Based Representation Learning. NeurIPS Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar
2024	J	`jnl`	Generative Intervention Models for Causal Perturbation Modeling. CoRR Nora Schneider, Lars Lorch, Niki Kilbertus, Bernhard Schölkopf, Andreas Krause
2024	A*	`conf`	Geometry-Aware Instrumental Variable Regression. ICML Heiner Kremer, Bernhard Schölkopf
2024	J	`jnl`	Geometry-Aware Instrumental Variable Regression. CoRR Heiner Kremer, Bernhard Schölkopf
2024	A*	`conf`	Ghost on the Shell: An Expressive Representation of General 3D Shapes. ICLR Zhen Liu, Yao Feng, Yuliang Xiu, Weiyang Liu, Liam Paull, Michael J. Black, Bernhard Schölkopf
2024	A*	`conf`	GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs. CVPR Gege Gao, Weiyang Liu, Anpei Chen, Andreas Geiger, Bernhard Schölkopf
2024	J	`jnl`	Hallmarks of Optimization Trajectories in Neural Networks and LLMs: The Lengths, Bends, and Dead Ends. CoRR Sidak Pal Singh, Bobby He, Thomas Hofmann, Bernhard Schölkopf
2024	J	`jnl`	Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning. CoRR Patrik Reizinger, Siyuan Guo, Ferenc Huszár, Bernhard Schölkopf, Wieland Brendel
2024	A*	`conf`	Identifying Policy Gradient Subspaces. ICLR Jan Schneider, Pierre Schumacher, Simon Guist, Le Chen, Daniel F. B. Haeufle, Bernhard Schölkopf, Dieter Büchler
2024	J	`jnl`	Identifying Policy Gradient Subspaces. CoRR Jan Schneider, Pierre Schumacher, Simon Guist, Le Chen, Daniel F. B. Häufle, Bernhard Schölkopf, Dieter Büchler
2024	J	`jnl`	Imagining and building wise machines: The centrality of AI metacognition. CoRR Samuel G. B. Johnson, Amir-Hossein Karimi, Yoshua Bengio, Nick Chater, Tobias Gerstenberg, Kate Larson, Sydney Levine, Melanie Mitchell, Iyad Rahwan, Bernhard Schölkopf, Igor Grossmann
2024	—	`conf`	Implicit Personalization in Language Models: A Systematic Study. EMNLP (Findings) Zhijing Jin, Nils Heil, Jiarui Liu, Shehzaad Dhuliawala, Yahang Qi, Bernhard Schölkopf, Rada Mihalcea, Mrinmaya Sachan
2024	J	`jnl`	Implicit Personalization in Language Models: A Systematic Study. CoRR Zhijing Jin, Nils Heil, Jiarui Liu, Shehzaad Dhuliawala, Yahang Qi, Bernhard Schölkopf, Rada Mihalcea, Mrinmaya Sachan
2024	J	`jnl`	Landscaping Linear Mode Connectivity. CoRR Sidak Pal Singh, Linara Adilova, Michael Kamp, Asja Fischer, Bernhard Schölkopf, Thomas Hofmann
2024	J	`jnl`	Language Models Can Reduce Asymmetry in Information Markets. CoRR Nasim Rahaman, Martin Weiss, Manuel Wüthrich, Yoshua Bengio, Li Erran Li, Chris Pal, Bernhard Schölkopf
2024	J	`jnl`	Learning Beyond Pattern Matching? Assaying Mathematical Understanding in LLMs. CoRR Siyuan Guo, Aniket Didolkar, Nan Rosemary Ke, Anirudh Goyal, Ferenc Huszár, Bernhard Schölkopf
2024	J	`jnl`	Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models. CoRR Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar
2024	J	`jnl`	Limits of Transformer Language Models on Learning Algorithmic Compositions. CoRR Jonathan Thomm, Aleksandar Terzic, Geethan Karunaratne, Giacomo Camposampiero, Bernhard Schölkopf, Abbas Rahimi
2024	A*	`conf`	Limits of Transformer Language Models on Learning to Compose Algorithms. NeurIPS Jonathan Thomm, Giacomo Camposampiero, Aleksandar Terzic, Michael Hersche, Bernhard Schölkopf, Abbas Rahimi
2024	J	`jnl`	Low-power scalable multilayer optoelectronic neural networks enabled with incoherent light. CoRR Alexander Song, Sai Nikhilesh Murty Kottapalli, Rahul Goyal, Bernhard Schölkopf, Peer Fischer
2024	J	`jnl`	MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs. CoRR Andreas Opedal, Haruki Shirakami, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan
2024	—	`conf`	Moûsai: Efficient Text-to-Music Diffusion Models. ACL (1) Flavio Schneider, Ojasv Kamal, Zhijing Jin, Bernhard Schölkopf
2024	J	`jnl`	Multilingual Trolley Problems for Language Models. CoRR Zhijing Jin, Sydney Levine, Max Kleiman-Weiner, Giorgio Piatti, Jiarui Liu, Fernando Gonzalez Adauto, Francesco Ortu, András Strausz, Mrinmaya Sachan, Rada Mihalcea, Yejin Choi, Bernhard Schölkopf
2024	A*	`conf`	On Affine Homotopy between Language Encoders. NeurIPS Robin Chan, Reda Boumasmoud, Anej Svete, Yuxin Ren, Qipeng Guo, Zhijing Jin, Shauli Ravfogel, Mrinmaya Sachan, Bernhard Schölkopf, Mennatallah El-Assady, Ryan Cotterell
2024	J	`jnl`	On Affine Homotopy between Language Encoders. CoRR Robin Chan, Reda Boumasmoud, Anej Svete, Yuxin Ren, Qipeng Guo, Zhijing Jin, Shauli Ravfogel, Mrinmaya Sachan, Bernhard Schölkopf, Mennatallah El-Assady, Ryan Cotterell
2024	J	`jnl`	On the Causal Nature of Sentiment Analysis. CoRR Zhiheng Lyu, Zhijing Jin, Fernando Gonzalez, Rada Mihalcea, Bernhard Schölkopf, Mrinmaya Sachan
2024	A*	`conf`	Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. ICRA Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew E. Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey T. Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante-Gomez, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Lin
2024	J	`jnl`	Optimal Decision Making Under Strategic Behavior. Manag. Sci. Stratis Tsirtsis, Behzad Tabibian, Moein Khajehnejad, Adish Singla, Bernhard Schölkopf, Manuel Gomez-Rodriguez
2024	A*	`conf`	Out-of-Variable Generalisation for Discriminative Models. ICLR Siyuan Guo, Jonas Bernhard Wildberger, Bernhard Schölkopf
2024	A*	`conf`	Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization. ICLR Weiyang Liu, Zeju Qiu, Yao Feng, Yuliang Xiu, Yuxuan Xue, Longhui Yu, Haiwen Feng, Zhen Liu, Juyeon Heo, Songyou Peng, Yandong Wen, Michael J. Black, Adrian Weller, Bernhard Schölkopf
2024	J	`jnl`	Preference Elicitation for Offline Reinforcement Learning. CoRR Alizée Pace, Bernhard Schölkopf, Gunnar Rätsch, Giorgia Ramponi
2024	A	`conf`	Products, Abstractions and Inclusions of Causal Spaces. UAI Simon Buchholz, Junhyung Park, Bernhard Schölkopf
2024	A*	`conf`	Provable Privacy with Non-Private Pre-Processing. ICML Yaxi Hu, Amartya Sanyal, Bernhard Schölkopf
2024	J	`jnl`	Provable Privacy with Non-Private Pre-Processing. CoRR Yaxi Hu, Amartya Sanyal, Bernhard Schölkopf
2024	J	`jnl`	RAVEN: Rethinking Adversarial Video Generation with Efficient Tri-plane Networks. CoRR Partha Ghosh, Soubhik Sanyal, Cordelia Schmid, Bernhard Schölkopf
2024	Misc	`conf`	RP1M: A Large-Scale Motion Dataset for Piano Playing with Bi-Manual Dexterous Robot Hands. CoRL Yi Zhao, Le Chen, Jan Schneider, Quankai Gao, Juho Kannala, Bernhard Schölkopf, Joni Pajarinen, Dieter Büchler
2024	J	`jnl`	RP1M: A Large-Scale Motion Dataset for Piano Playing with Bi-Manual Dexterous Robot Hands. CoRR Yi Zhao, Le Chen, Jan Schneider, Quankai Gao, Juho Kannala, Bernhard Schölkopf, Joni Pajarinen, Dieter Büchler
2024	J	`jnl`	Real-time gravitational-wave inference for binary neutron stars using machine learning. CoRR Maximilian Dax, Stephen R. Green, Jonathan Gair, Nihar Gupte, Michael Pürrer, Vivien Raymond, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
2024	A*	`conf`	Robustness of Nonlinear Representation Learning. ICML Simon Buchholz, Bernhard Schölkopf
2024	J	`jnl`	SPARTAN: A Sparse Transformer Learning Local Causation. CoRR Anson Lei, Bernhard Schölkopf, Ingmar Posner
2024	—	`conf`	Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion. Robotics: Science and Systems Simon Guist, Jan Schneider, Hao Ma, Le Chen, Vincent Berenz, Julian Martus, Heiko Ott, Felix Grüninger, Michael Muehlebach, Jonathan Fiene, Bernhard Schölkopf, Dieter Büchler
2024	A*	`conf`	Skill or Luck? Return Decomposition via Advantage Functions. ICLR Hsiao-Ru Pan, Bernhard Schölkopf
2024	J	`jnl`	Skill or Luck? Return Decomposition via Advantage Functions. CoRR Hsiao-Ru Pan, Bernhard Schölkopf
2024	J	`jnl`	Standardizing Structural Causal Models. CoRR Weronika Ormaniec, Scott Sussex, Lars Lorch, Bernhard Schölkopf, Andreas Krause
2024	A	`conf`	Targeted Reduction of Causal Models. UAI Armin Kekic, Bernhard Schölkopf, Michel Besserve
2024	—	`conf`	Terminating Differentiable Tree Experts. NeSy (1) Jonathan Thomm, Michael Hersche, Giacomo Camposampiero, Aleksandar Terzic, Bernhard Schölkopf, Abbas Rahimi
2024	J	`jnl`	Terminating Differentiable Tree Experts. CoRR Jonathan Thomm, Michael Hersche, Giacomo Camposampiero, Aleksandar Terzic, Bernhard Schölkopf, Abbas Rahimi
2024	J	`jnl`	The Essential Role of Causality in Foundation World Models for Embodied AI. CoRR Tarun Gupta, Wenbo Gong, Chao Ma, Nick Pawlowski, Agrin Hilmkil, Meyer Scetbon, Ade Famoti, Ashley Juan Llorens, Jianfeng Gao, Stefan Bauer, Danica Kragic, Bernhard Schölkopf, Cheng Zhang
2024	A*	`conf`	The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks. ICLR Aaron Spieler, Nasim Rahaman, Georg Martius, Bernhard Schölkopf, Anna Levina
2024	A*	`conf`	The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoning. EMNLP Shaobo Cui, Zhijing Jin, Bernhard Schölkopf, Boi Faltings
2024	J	`jnl`	The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoning. CoRR Shaobo Cui, Zhijing Jin, Bernhard Schölkopf, Boi Faltings
2024	J	`jnl`	Towards fully covariant machine learning. Trans. Mach. Learn. Res. Soledad Villar, David W. Hogg, Weichi Yao, George A. Kevrekidis, Bernhard Schölkopf
2024	J	`jnl`	Verbalized Machine Learning: Revisiting Machine Learning with Language Models. CoRR Tim Z. Xiao, Robert Bamler, Bernhard Schölkopf, Weiyang Liu
2023	—	`conf`	A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models. ACL (1) Alessandro Stolfo, Zhijing Jin, Kumar Shridhar, Bernhard Schölkopf, Mrinmaya Sachan
2023	A*	`conf`	A Measure-Theoretic Axiomatisation of Causality. NeurIPS Junhyung Park, Simon Buchholz, Bernhard Schölkopf, Krikamol Muandet
2023	J	`jnl`	A Measure-Theoretic Axiomatisation of Causality. CoRR Junhyung Park, Simon Buchholz, Bernhard Schölkopf, Krikamol Muandet
2023	J	`jnl`	A Robust Open-source Tendon-driven Robot Arm for Learning Control of Dynamic Motions. CoRR Simon Guist, Jan Schneider, Hao Ma, Vincent Berenz, Julian Martus, Felix Grüninger, Michael Mühlebach, Jonathan Fiene, Bernhard Schölkopf, Dieter Büchler
2023	J	`jnl`	A Survey of Algorithmic Recourse: Contrastive Explanations and Consequential Recommendations. ACM Comput. Surv. Amir-Hossein Karimi, Gilles Barthe, Bernhard Schölkopf, Isabel Valera
2023	J	`jnl`	A machine learning route between band mapping and band structure. Nat. Comput. Sci. R. Patrick Xian, Vincent Stimper, Marios Zacharias, Maciej Dendzik, Shuo Dong, Samuel Beaulieu, Bernhard Schölkopf, Martin Wolf, Laurenz Rettig, Christian Carbogno, Stefan Bauer, Ralph Ernstorfer
2023	A*	`conf`	AIMY: An Open-source Table Tennis Ball Launcher for Versatile and High-fidelity Trajectory Generation. ICRA Alexander Dittrich, Jan Schneider, Simon Guist, Nico Gürtler, Heiko Ott, Thomas Steinbrenner, Bernhard Schölkopf, Dieter Büchler
2023	J	`jnl`	All Roads Lead to Rome? Exploring the Invariance of Transformers' Representations. CoRR Yuxin Ren, Qipeng Guo, Zhijing Jin, Shauli Ravfogel, Mrinmaya Sachan, Bernhard Schölkopf, Ryan Cotterell
2023	A	`conf`	BaCaDI: Bayesian Causal Discovery with Unknown Interventions. AISTATS Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause
2023	A*	`conf`	Benchmarking Offline Reinforcement Learning on Real-Robot Hardware. ICLR Nico Gürtler, Sebastian Blaes, Pavel Kolev, Felix Widmaier, Manuel Wuthrich, Stefan Bauer, Bernhard Schölkopf, Georg Martius
2023	J	`jnl`	Benchmarking Offline Reinforcement Learning on Real-Robot Hardware. CoRR Nico Gürtler, Sebastian Blaes, Pavel Kolev, Felix Widmaier, Manuel Wüthrich, Stefan Bauer, Bernhard Schölkopf, Georg Martius
2023	—	`conf`	Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good. EMNLP (Findings) Fernando Gonzalez Adauto, Zhijing Jin, Bernhard Schölkopf, Tom Hope, Mrinmaya Sachan, Rada Mihalcea
2023	J	`jnl`	Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good. CoRR Fernando Gonzalez, Zhijing Jin, Bernhard Schölkopf, Tom Hope, Mrinmaya Sachan, Rada Mihalcea
2023	J	`jnl`	Borges and AI. CoRR Léon Bottou, Bernhard Schölkopf
2023	A*	`conf`	Bridging the Gap to Real-World Object-Centric Learning. ICLR Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, Francesco Locatello
2023	A*	`conf`	CLadder: A Benchmark to Assess Causal Reasoning Capabilities of Language Models. NeurIPS Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, Zhiheng Lyu, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, Bernhard Schölkopf
2023	J	`jnl`	CLadder: A Benchmark to Assess Causal Reasoning Capabilities of Language Models. CoRR Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, Zhiheng Lyu, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, Bernhard Schölkopf
2023	J	`jnl`	Can Large Language Models Infer Causation from Correlation? CoRR Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona T. Diab, Bernhard Schölkopf
2023	A*	`conf`	Causal Component Analysis. NeurIPS Wendong Liang, Armin Kekic, Julius von Kügelgen, Simon Buchholz, Michel Besserve, Luigi Gresele, Bernhard Schölkopf
2023	J	`jnl`	Causal Component Analysis. CoRR Wendong Liang, Armin Kekic, Julius von Kügelgen, Simon Buchholz, Michel Besserve, Luigi Gresele, Bernhard Schölkopf
2023	J	`jnl`	Causal Effect Estimation from Observational and Interventional Data Through Matrix Weighted Linear Estimators. CoRR Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach
2023	J	`jnl`	Causal Modeling with Stationary Diffusions. CoRR Lars Lorch, Andreas Krause, Bernhard Schölkopf
2023	—	`conf`	Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning. CLeaR Yuejiang Liu, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello
2023	J	`jnl`	Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning. CoRR Yuejiang Liu, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello
2023	A*	`conf`	Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data. NeurIPS Siyuan Guo, Viktor Tóth, Bernhard Schölkopf, Ferenc Huszar
2023	A	`conf`	Causal effect estimation from observational and interventional data through matrix weighted linear estimators. UAI Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach
2023	J	`jnl`	CausalCite: A Causal Formulation of Paper Citations. CoRR Ishan Kumar, Zhijing Jin, Ehsan Mokhtarian, Siyuan Guo, Yuen Chen, Negar Kiyavash, Mrinmaya Sachan, Bernhard Schölkopf
2023	A*	`conf`	Controlling Text-to-Image Diffusion by Orthogonal Finetuning. NeurIPS Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf
2023	J	`jnl`	Controlling Text-to-Image Diffusion by Orthogonal Finetuning. CoRR Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf
2023	A*	`conf`	DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability. ICLR Cian Eastwood, Andrei Liviu Nicolicioiu, Julius von Kügelgen, Armin Kekic, Frederik Träuble, Andrea Dittadi, Bernhard Schölkopf
2023	A	`conf`	Data-Efficient Online Learning of Ball Placement in Robot Table Tennis. IROS Philip Tobuschat, Hao Ma, Dieter Büchler, Bernhard Schölkopf, Michael Muehlebach
2023	J	`jnl`	Data-Efficient Online Learning of Ball Placement in Robot Table Tennis. CoRR Philip Tobuschat, Hao Ma, Dieter Büchler, Bernhard Schölkopf, Michael Muehlebach
2023	B	`conf`	Dataflow graphs as complete causal graphs. CAIN Andrei Paleyes, Siyuan Guo, Bernhard Schölkopf, Neil D. Lawrence
2023	J	`jnl`	Dataflow graphs as complete causal graphs. CoRR Andrei Paleyes, Siyuan Guo, Bernhard Schölkopf, Neil D. Lawrence
2023	J	`jnl`	Deep Backtracking Counterfactuals for Causally Compliant Explanations. CoRR Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach
2023	J	`jnl`	Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding. CoRR Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Rätsch, Guy Tennenholtz
2023	A*	`conf`	Diffusion Based Representation Learning. ICML Sarthak Mittal, Korbinian Abstreiter, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou
2023	A*	`conf`	Discrete Key-Value Bottleneck. ICML Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf
2023	A*	`conf`	Estimation Beyond Data Reweighting: Kernel Method of Moments. ICML Heiner Kremer, Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu
2023	J	`jnl`	Estimation Beyond Data Reweighting: Kernel Method of Moments. CoRR Heiner Kremer, Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu
2023	J	`jnl`	Evaluating vaccine allocation strategies using simulation-assisted causal modeling. Patterns Armin Kekic, Jonas Dehning, Luigi Gresele, Julius von Kügelgen, Viola Priesemann, Bernhard Schölkopf
2023	A*	`conf`	Flow Annealed Importance Sampling Bootstrap. ICLR Laurence Illing Midgley, Vincent Stimper, Gregor N. C. Simm, Bernhard Schölkopf, José Miguel Hernández-Lobato
2023	A*	`conf`	Flow Matching for Scalable Simulation-Based Inference. NeurIPS Jonas Wildberger, Maximilian Dax, Simon Buchholz, Stephen R. Green, Jakob H. Macke, Bernhard Schölkopf
2023	J	`jnl`	Flow Matching for Scalable Simulation-Based Inference. CoRR Maximilian Dax, Jonas Wildberger, Simon Buchholz, Stephen R. Green, Jakob H. Macke, Bernhard Schölkopf
2023	A*	`conf`	Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap. ICLR Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schölkopf
2023	J	`jnl`	Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap. CoRR Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schölkopf
2023	J	`jnl`	Ghost on the Shell: An Expressive Representation of General 3D Shapes. CoRR Zhen Liu, Yao Feng, Yuliang Xiu, Weiyang Liu, Liam Paull, Michael J. Black, Bernhard Schölkopf
2023	B	`conf`	Glare Removal for Astronomical Images with High Local Dynamic Range. ICCP Max-Olivier Van Bastelaer, Heiner Kremer, Valentin Volchkov, Jean-Claude Passy, Bernhard Schölkopf
2023	J	`jnl`	GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs. CoRR Gege Gao, Weiyang Liu, Anpei Chen, Andreas Geiger, Bernhard Schölkopf
2023	—	`conf`	Hindsight States: Blending Sim & Real Task Elements for Efficient Reinforcement Learning. Robotics: Science and Systems Simon Guist, Jan Schneider, Vincent Berenz, Alexander Dittrich, Bernhard Schölkopf, Dieter Büchler
2023	J	`jnl`	Hindsight States: Blending Sim and Real Task Elements for Efficient Reinforcement Learning. CoRR Simon Guist, Jan Schneider, Alexander Dittrich, Vincent Berenz, Bernhard Schölkopf, Dieter Büchler
2023	A*	`conf`	Homomorphism AutoEncoder - Learning Group Structured Representations from Observed Transitions. ICML Hamza Keurti, Hsiao-Ru Pan, Michel Besserve, Benjamin F. Grewe, Bernhard Schölkopf
2023	J	`jnl`	Independent Mechanism Analysis and the Manifold Hypothesis. CoRR Shubhangi Ghosh, Luigi Gresele, Julius von Kügelgen, Michel Besserve, Bernhard Schölkopf
2023	J	`jnl`	Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling. CoRR Timothy D. Gebhard, Jonas Wildberger, Maximilian Dax, Daniel Angerhausen, Sascha P. Quanz, Bernhard Schölkopf
2023	J	`jnl`	Investigating the Impact of Action Representations in Policy Gradient Algorithms. CoRR Jan Schneider, Pierre Schumacher, Daniel F. B. Häufle, Bernhard Schölkopf, Dieter Büchler
2023	A	`conf`	Iterative Teaching by Data Hallucination. AISTATS Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf
2023	J	`jnl`	Jacobian-based Causal Discovery with Nonlinear ICA. Trans. Mach. Learn. Res. Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel
2023	J	`jnl`	Kernel-Based Independence Tests for Causal Structure Learning on Functional Data. Entropy Felix Laumann, Julius von Kügelgen, Junhyung Park, Bernhard Schölkopf, Mauricio Barahona
2023	A*	`conf`	Learning Linear Causal Representations from Interventions under General Nonlinear Mixing. NeurIPS Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar
2023	J	`jnl`	Learning Linear Causal Representations from Interventions under General Nonlinear Mixing. CoRR Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar
2023	—	`conf`	Learning Locomotion Skills from MPC in Sensor Space. L4DC Majid Khadiv, Avadesh Meduri, Huaijiang Zhu, Ludovic Righetti, Bernhard Schölkopf
2023	A*	`conf`	Leveraging sparse and shared feature activations for disentangled representation learning. NeurIPS Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
2023	J	`jnl`	Leveraging sparse and shared feature activations for disentangled representation learning. CoRR Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
2023	—	`conf`	Membership Inference Attacks against Language Models via Neighbourhood Comparison. ACL (Findings) Justus Mattern, Fatemehsadat Mireshghallah, Zhijing Jin, Bernhard Schölkopf, Mrinmaya Sachan, Taylor Berg-Kirkpatrick
2023	J	`jnl`	Membership Inference Attacks against Language Models via Neighbourhood Comparison. CoRR Justus Mattern, Fatemehsadat Mireshghallah, Zhijing Jin, Bernhard Schölkopf, Mrinmaya Sachan, Taylor Berg-Kirkpatrick
2023	J	`jnl`	Metrizing Weak Convergence with Maximum Mean Discrepancies. J. Mach. Learn. Res. Carl-Johann Simon-Gabriel, Alessandro Barp, Bernhard Schölkopf, Lester Mackey
2023	J	`jnl`	Moûsai: Text-to-Music Generation with Long-Context Latent Diffusion. CoRR Flavio Schneider, Zhijing Jin, Bernhard Schölkopf
2023	J	`jnl`	Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures. CoRR David F. Jenny, Yann Billeter, Mrinmaya Sachan, Bernhard Schölkopf, Zhijing Jin
2023	J	`jnl`	Neural Causal Structure Discovery from Interventions. Trans. Mach. Learn. Res. Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio
2023	A*	`conf`	Nonparametric Identifiability of Causal Representations from Unknown Interventions. NeurIPS Julius von Kügelgen, Michel Besserve, Wendong Liang, Luigi Gresele, Armin Kekic, Elias Bareinboim, David M. Blei, Bernhard Schölkopf
2023	J	`jnl`	Nonparametric Identifiability of Causal Representations from Unknown Interventions. CoRR Julius von Kügelgen, Michel Besserve, Wendong Liang, Luigi Gresele, Armin Kekic, Elias Bareinboim, David M. Blei, Bernhard Schölkopf
2023	A*	`conf`	On Data Manifolds Entailed by Structural Causal Models. ICML Ricardo Dominguez-Olmedo, Amir-Hossein Karimi, Georgios Arvanitidis, Bernhard Schölkopf
2023	A*	`conf`	On the Identifiability and Estimation of Causal Location-Scale Noise Models. ICML Alexander Immer, Christoph Schultheiss, Julia E. Vogt, Bernhard Schölkopf, Peter Bühlmann, Alexander Marx
2023	—	`conf`	On the Interventional Kullback-Leibler Divergence. CLeaR Jonas Bernhard Wildberger, Siyuan Guo, Arnab Bhattacharyya, Bernhard Schölkopf
2023	J	`jnl`	On the Interventional Kullback-Leibler Divergence. CoRR Jonas Wildberger, Siyuan Guo, Arnab Bhattacharyya, Bernhard Schölkopf
2023	A*	`conf`	On the Relationship Between Explanation and Prediction: A Causal View. ICML Amir-Hossein Karimi, Krikamol Muandet, Simon Kornblith, Bernhard Schölkopf, Been Kim
2023	J	`jnl`	Open X-Embodiment: Robotic Learning Datasets and RT-X Models. CoRR Open X.-Embodiment Collaboration, Abhishek Padalkar, Acorn Pooley, Ajinkya Jain, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Raj, Anikait Singh, Anthony Brohan, Antonin Raffin, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Brian Ichter, Cewu Lu, Charles Xu, Chelsea Finn, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Chuer Pan, Chuyuan Fu, Coline Devin, Danny Driess, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Federico Ceola, Fei Xia, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Giulio Schiavi, Gregory Kahn, Hao Su, Haoshu Fang, Haochen Shi, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Igor Mordatch, Ilija Radosavovic, et al.
2023	J	`jnl`	Out-of-Variable Generalization. CoRR Siyuan Guo, Jonas Wildberger, Bernhard Schölkopf
2023	A*	`conf`	Pairwise Similarity Learning is SimPLE. ICCV Yandong Wen, Weiyang Liu, Yao Feng, Bhiksha Raj, Rita Singh, Adrian Weller, Michael J. Black, Bernhard Schölkopf
2023	J	`jnl`	Pairwise Similarity Learning is SimPLE. CoRR Yandong Wen, Weiyang Liu, Yao Feng, Bhiksha Raj, Rita Singh, Adrian Weller, Michael J. Black, Bernhard Schölkopf
2023	J	`jnl`	Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization. CoRR Weiyang Liu, Zeju Qiu, Yao Feng, Yuliang Xiu, Yuxuan Xue, Longhui Yu, Haiwen Feng, Zhen Liu, Juyeon Heo, Songyou Peng, Yandong Wen, Michael J. Black, Adrian Weller, Bernhard Schölkopf
2023	J	`jnl`	Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks. CoRR Timothy D. Gebhard, Daniel Angerhausen, Björn S. Konrad, Eleonora Alei, Sascha P. Quanz, Bernhard Schölkopf
2023	J	`jnl`	Posterior Annealing: Fast Calibrated Uncertainty for Regression. CoRR Uddeshya Upadhyay, Jae-Myung Kim, Cordelia Schmid, Bernhard Schölkopf, Zeynep Akata
2023	A*	`conf`	Provably Learning Object-Centric Representations. ICML Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius von Kügelgen, Wieland Brendel
2023	J	`jnl`	Provably Learning Object-Centric Representations. CoRR Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius von Kügelgen, Wieland Brendel
2023	J	`jnl`	Psychologically-Inspired Causal Prompts. CoRR Zhiheng Lyu, Zhijing Jin, Justus Mattern, Rada Mihalcea, Mrinmaya Sachan, Bernhard Schölkopf
2023	J	`jnl`	Pyfectious: An individual-level simulator to discover optimal containment policies for epidemic diseases. PLoS Comput. Biol. Arash Mehrjou, Ashkan Soleymani, Amin Abyaneh, Samir Bhatt, Bernhard Schölkopf, Stefan Bauer
2023	J	`jnl`	Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World. CoRR Nico Gürtler, Felix Widmaier, Cansu Sancaktar, Sebastian Blaes, Pavel Kolev, Stefan Bauer, Manuel Wüthrich, Markus Wulfmeier, Martin A. Riedmiller, Arthur Allshire, Qiang Wang, Robert McCarthy, Hangyeol Kim, Jongchan Baek, Wookyong Kwon, Shanliang Qian, Yasunori Toshimitsu, Mike Yan Michelis, Amirhossein Kazemipour, Arman Raayatsanati, Hehui Zheng, Barnabas Gavin Cangan, Bernhard Schölkopf, Georg Martius
2023	J	`jnl`	Reinforcement learning with model-based feedforward inputs for robotic table tennis. Auton. Robots Hao Ma, Dieter Büchler, Bernhard Schölkopf, Michael Muehlebach
2023	J	`jnl`	ResMiCo: Increasing the quality of metagenome-assembled genomes with deep learning. PLoS Comput. Biol. Olga Mineeva, Daniel Danciu, Bernhard Schölkopf, Ruth E. Ley, Gunnar Rätsch, Nicholas D. Youngblut
2023	—	`conf`	Robustness Implies Fairness in Causal Algorithmic Recourse. FAccT Ahmad-Reza Ehyaei, Amir-Hossein Karimi, Bernhard Schölkopf, Setareh Maghsudi
2023	J	`jnl`	Robustness Implies Fairness in Causal Algorithmic Recourse. CoRR Ahmad-Reza Ehyaei, Amir-Hossein Karimi, Bernhard Schölkopf, Setareh Maghsudi
2023	A*	`conf`	SE(3) Equivariant Augmented Coupling Flows. NeurIPS Laurence I. Midgley, Vincent Stimper, Javier Antorán, Emile Mathieu, Bernhard Schölkopf, José Miguel Hernández-Lobato
2023	J	`jnl`	SE(3) Equivariant Augmented Coupling Flows. CoRR Laurence I. Midgley, Vincent Stimper, Javier Antorán, Emile Mathieu, Bernhard Schölkopf, José Miguel Hernández-Lobato
2023	J	`jnl`	Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations. CoRR Cian Eastwood, Julius von Kügelgen, Linus Ericsson, Diane Bouchacourt, Pascal Vincent, Bernhard Schölkopf, Mark Ibrahim
2023	A*	`conf`	Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to Harness Spurious Features. NeurIPS Cian Eastwood, Shashank Singh, Andrei Liviu Nicolicioiu, Marin Vlastelica Pogancic, Julius von Kügelgen, Bernhard Schölkopf
2023	J	`jnl`	Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to Harness Spurious Features. CoRR Cian Eastwood, Shashank Singh, Andrei Liviu Nicolicioiu, Marin Vlastelica, Julius von Kügelgen, Bernhard Schölkopf
2023	A*	`conf`	Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels. ICML Alexander Immer, Tycho F. A. van der Ouderaa, Mark van der Wilk, Gunnar Rätsch, Bernhard Schölkopf
2023	J	`jnl`	Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels. CoRR Alexander Immer, Tycho F. A. van der Ouderaa, Mark van der Wilk, Gunnar Rätsch, Bernhard Schölkopf
2023	A*	`conf`	Structure by Architecture: Structured Representations without Regularization. ICLR Felix Leeb, Giulia Lanzillotta, Yashas Annadani, Michel Besserve, Stefan Bauer, Bernhard Schölkopf
2023	J	`jnl`	Synchronizing Machine Learning Algorithms, Realtime Robotic Control and Simulated Environment with o80. CoRR Vincent Berenz, Felix Widmaier, Simon Guist, Bernhard Schölkopf, Dieter Büchler
2023	J	`jnl`	Targeted Reduction of Causal Models. CoRR Armin Kekic, Bernhard Schölkopf, Michel Besserve
2023	J	`jnl`	The ELM Neuron: an Efficient and Expressive Cortical Neuron Model Can Solve Long-Horizon Tasks. CoRR Aaron Spieler, Nasim Rahaman, Georg Martius, Bernhard Schölkopf, Anna Levina
2023	A*	`conf`	The Hessian perspective into the Nature of Convolutional Neural Networks. ICML Sidak Pal Singh, Thomas Hofmann, Bernhard Schölkopf
2023	J	`jnl`	The Hessian perspective into the Nature of Convolutional Neural Networks. CoRR Sidak Pal Singh, Thomas Hofmann, Bernhard Schölkopf
2023	J	`jnl`	The passive symmetries of machine learning. CoRR Soledad Villar, David W. Hogg, Weichi Yao, George A. Kevrekidis, Bernhard Schölkopf
2023	—	`conf`	Unsupervised Object Learning via Common Fate. CLeaR Matthias Tangemann, Steffen Schneider, Julius von Kügelgen, Francesco Locatello, Peter Vincent Gehler, Thomas Brox, Matthias Kümmerer, Matthias Bethge, Bernhard Schölkopf
2023	J	`jnl`	Variational Causal Dynamics: Discovering Modular World Models from Interventions. Trans. Mach. Learn. Res. Anson Lei, Bernhard Schölkopf, Ingmar Posner
2023	J	`jnl`	Voices of Her: Analyzing Gender Differences in the AI Publication World. CoRR Yiwen Ding, Jiarui Liu, Zhiheng Lyu, Kun Zhang, Bernhard Schölkopf, Zhijing Jin, Rada Mihalcea
2023	J	`jnl`	normflows: A PyTorch Package for Normalizing Flows. CoRR Vincent Stimper, David Liu, Andrew Campbell, Vincent Berenz, Lukas Ryll, Bernhard Schölkopf, José Miguel Hernández-Lobato
2023	J	`jnl`	normflows: A PyTorch Package for Normalizing Flows. J. Open Source Softw. Vincent Stimper, David Liu, Andrew Campbell, Vincent Berenz, Lukas Ryll, Bernhard Schölkopf, José Miguel Hernández-Lobato
2022	—	`ed.`	1st Conference on Causal Learning and Reasoning, CLeaR 2022, Sequoia Conference Center, Eureka, CA, USA, 11-13 April, 2022 CLeaR Bernhard Schölkopf, Caroline Uhler, Kun Zhang
2022	J	`jnl`	A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models. CoRR Alessandro Stolfo, Zhijing Jin, Kumar Shridhar, Bernhard Schölkopf, Mrinmaya Sachan
2022	J	`jnl`	A General Purpose Neural Architecture for Geospatial Systems. CoRR Nasim Rahaman, Martin Weiss, Frederik Träuble, Francesco Locatello, Alexandre Lacoste, Yoshua Bengio, Chris Pal, Li Erran Li, Bernhard Schölkopf
2022	—	`conf`	A Learning-based Iterative Control Framework for Controlling a Robot Arm with Pneumatic Artificial Muscles. Robotics: Science and Systems Hao Ma, Dieter Büchler, Bernhard Schölkopf, Michael Muehlebach
2022	A	`conf`	A Witness Two-Sample Test. AISTATS Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
2022	A	`conf`	A prior-based approximate latent Riemannian metric. AISTATS Georgios Arvanitidis, Bogdan M. Georgiev, Bernhard Schölkopf
2022	J	`jnl`	AIMY: An Open-source Table Tennis Ball Launcher for Versatile and High-fidelity Trajectory Generation. CoRR Alexander Dittrich, Jan Schneider, Simon Guist, Bernhard Schölkopf, Dieter Büchler
2022	A*	`conf`	Action-Sufficient State Representation Learning for Control with Structural Constraints. ICML Biwei Huang, Chaochao Lu, Liu Leqi, José Miguel Hernández-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang
2022	J	`jnl`	Adapting to noise distribution shifts in flow-based gravitational-wave inference. CoRR Jonas Wildberger, Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
2022	A*	`conf`	Adversarial Robustness Through the Lens of Causality. ICLR Yonggang Zhang, Mingming Gong, Tongliang Liu, Gang Niu, Xinmei Tian, Bo Han, Bernhard Schölkopf, Kun Zhang
2022	A	`conf`	Adversarially Robust Kernel Smoothing. AISTATS Jia-Jie Zhu, Christina Kouridi, Yassine Nemmour, Bernhard Schölkopf
2022	A*	`conf`	Amortized Inference for Causal Structure Learning. NeurIPS Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf
2022	J	`jnl`	Amortized Inference for Causal Structure Learning. CoRR Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf
2022	A*	`conf`	Assaying Out-Of-Distribution Generalization in Transfer Learning. NeurIPS Florian Wenzel, Andrea Dittadi, Peter V. Gehler, Carl-Johann Simon-Gabriel, Max Horn, Dominik Zietlow, David Kernert, Chris Russell, Thomas Brox, Bernt Schiele, Bernhard Schölkopf, Francesco Locatello
2022	J	`jnl`	Assaying Out-Of-Distribution Generalization in Transfer Learning. CoRR Florian Wenzel, Andrea Dittadi, Peter Vincent Gehler, Carl-Johann Simon-Gabriel, Max Horn, Dominik Zietlow, David Kernert, Chris Russell, Thomas Brox, Bernt Schiele, Bernhard Schölkopf, Francesco Locatello
2022	A*	`conf`	AutoML Two-Sample Test. NeurIPS Jonas M. Kübler, Vincent Stimper, Simon Buchholz, Krikamol Muandet, Bernhard Schölkopf
2022	J	`jnl`	AutoML Two-Sample Test. CoRR Jonas M. Kübler, Vincent Stimper, Simon Buchholz, Krikamol Muandet, Bernhard Schölkopf
2022	J	`jnl`	BaCaDI: Bayesian Causal Discovery with Unknown Interventions. CoRR Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause
2022	J	`jnl`	Bridging the Gap to Real-World Object-Centric Learning. CoRR Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, Francesco Locatello
2022	A*	`conf`	Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis. NeurIPS Ronan Perry, Julius von Kügelgen, Bernhard Schölkopf
2022	J	`jnl`	Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis. CoRR Ronan Perry, Julius von Kügelgen, Bernhard Schölkopf
2022	J	`jnl`	Causal Feature Selection via Orthogonal Search. Trans. Mach. Learn. Res. Ashkan Soleymani, Anant Raj, Stefan Bauer, Bernhard Schölkopf, Michel Besserve
2022	A*	`conf`	Causal Inference Through the Structural Causal Marginal Problem. ICML Luigi Gresele, Julius von Kügelgen, Jonas M. Kübler, Elke Kirschbaum, Bernhard Schölkopf, Dominik Janzing
2022	J	`jnl`	Causal Inference Through the Structural Causal Marginal Problem. CoRR Luigi Gresele, Julius von Kügelgen, Jonas M. Kübler, Elke Kirschbaum, Bernhard Schölkopf, Dominik Janzing
2022	J	`jnl`	Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data. CoRR Siyuan Guo, Viktor Tóth, Bernhard Schölkopf, Ferenc Huszár
2022	—	`ch.`	Causality for Machine Learning. Probabilistic and Causal Inference Bernhard Schölkopf
2022	—	`conf`	Cause-effect inference through spectral independence in linear dynamical systems: theoretical foundations. CLeaR Michel Besserve, Naji Shajarisales, Dominik Janzing, Bernhard Schölkopf
2022	J	`jnl`	Compositional Multi-Object Reinforcement Learning with Linear Relation Networks. CoRR Davide Mambelli, Frederik Träuble, Stefan Bauer, Bernhard Schölkopf, Francesco Locatello
2022	J	`jnl`	DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability. CoRR Cian Eastwood, Andrei Liviu Nicolicioiu, Julius von Kügelgen, Armin Kekic, Frederik Träuble, Andrea Dittadi, Bernhard Schölkopf
2022	A*	`conf`	Differentially Private Language Models for Secure Data Sharing. EMNLP Justus Mattern, Zhijing Jin, Benjamin Weggenmann, Bernhard Schölkopf, Mrinmaya Sachan
2022	J	`jnl`	Differentially Private Language Models for Secure Data Sharing. CoRR Justus Mattern, Zhijing Jin, Benjamin Weggenmann, Bernhard Schölkopf, Mrinmaya Sachan
2022	A*	`conf`	Direct Advantage Estimation. NeurIPS Hsiao-Ru Pan, Nico Gürtler, Alexander Neitz, Bernhard Schölkopf
2022	J	`jnl`	Discrete Key-Value Bottleneck. CoRR Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf
2022	A*	`conf`	Embrace the Gap: VAEs Perform Independent Mechanism Analysis. NeurIPS Patrik Reizinger, Luigi Gresele, Jack Brady, Julius von Kügelgen, Dominik Zietlow, Bernhard Schölkopf, Georg Martius, Wieland Brendel, Michel Besserve
2022	J	`jnl`	Embrace the Gap: VAEs Perform Independent Mechanism Analysis. CoRR Patrik Reizinger, Luigi Gresele, Jack Brady, Julius von Kügelgen, Dominik Zietlow, Bernhard Schölkopf, Georg Martius, Wieland Brendel, Michel Besserve
2022	J	`jnl`	Evaluating vaccine allocation strategies using simulation-assisted causal modelling. CoRR Armin Kekic, Jonas Dehning, Luigi Gresele, Julius von Kügelgen, Viola Priesemann, Bernhard Schölkopf
2022	A*	`conf`	Exploring the Latent Space of Autoencoders with Interventional Assays. NeurIPS Felix Leeb, Stefan Bauer, Michel Besserve, Bernhard Schölkopf
2022	J	`jnl`	FED-CD: Federated Causal Discovery from Interventional and Observational Data. CoRR Amin Abyaneh, Nino Scherrer, Patrick Schwab, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou
2022	J	`jnl`	Flow Annealed Importance Sampling Bootstrap. CoRR Laurence Illing Midgley, Vincent Stimper, Gregor N. C. Simm, Bernhard Schölkopf, José Miguel Hernández-Lobato
2022	J	`jnl`	From Statistical to Causal Learning. CoRR Bernhard Schölkopf, Julius von Kügelgen
2022	A*	`conf`	Function Classes for Identifiable Nonlinear Independent Component Analysis. NeurIPS Simon Buchholz, Michel Besserve, Bernhard Schölkopf
2022	J	`jnl`	Function Classes for Identifiable Nonlinear Independent Component Analysis. CoRR Simon Buchholz, Michel Besserve, Bernhard Schölkopf
2022	A*	`conf`	Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions. ICML Heiner Kremer, Jia-Jie Zhu, Krikamol Muandet, Bernhard Schölkopf
2022	J	`jnl`	Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions. CoRR Heiner Kremer, Jia-Jie Zhu, Krikamol Muandet, Bernhard Schölkopf
2022	A	`conf`	GalilAI: Out-of-Task Distribution Detection using Causal Active Experimentation for Safe Transfer RL. AISTATS Sumedh A. Sontakke, Stephen Iota, Zizhao Hu, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf
2022	A*	`conf`	Generalization and Robustness Implications in Object-Centric Learning. ICML Andrea Dittadi, Samuele S. Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello
2022	A*	`conf`	Group equivariant neural posterior estimation. ICLR Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Deistler, Bernhard Schölkopf, Jakob H. Macke
2022	J	`jnl`	Half-sibling regression meets exoplanet imaging: PSF modeling and subtraction using a flexible, domain knowledge-driven, causal framework. CoRR Timothy D. Gebhard, Markus J. Bonse, Sascha P. Quanz, Bernhard Schölkopf
2022	J	`jnl`	Homomorphism Autoencoder - Learning Group Structured Representations from Observed Transitions. CoRR Hamza Keurti, Hsiao-Ru Pan, Michel Besserve, Benjamin F. Grewe, Bernhard Schölkopf
2022	A*	`conf`	Interventions, Where and How? Experimental Design for Causal Models at Scale. NeurIPS Panagiotis Tigas, Yashas Annadani, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer
2022	J	`jnl`	Interventions, Where and How? Experimental Design for Causal Models at Scale. CoRR Panagiotis Tigas, Yashas Annadani, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer
2022	A*	`conf`	Invariant Causal Representation Learning for Out-of-Distribution Generalization. ICLR Chaochao Lu, Yuhuai Wu, José Miguel Hernández-Lobato, Bernhard Schölkopf
2022	J	`jnl`	Iterative Teaching by Data Hallucination. CoRR Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf
2022	—	`conf`	Learning Random Feature Dynamics for Uncertainty Quantification. CDC Diego Agudelo-España, Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu
2022	A	`conf`	Learning soft interventions in complex equilibrium systems. UAI Michel Besserve, Bernhard Schölkopf
2022	J	`jnl`	Learning to Play Table Tennis From Scratch Using Muscular Robots. IEEE Trans. Robotics Dieter Büchler, Simon Guist, Roberto Calandra, Vincent Berenz, Bernhard Schölkopf, Jan Peters
2022	A*	`conf`	Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers. CVPR Dominik Zietlow, Michael Lohaus, Guha Balakrishnan, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Chris Russell
2022	J	`jnl`	Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers. CoRR Dominik Zietlow, Michael Lohaus, Guha Balakrishnan, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Chris Russell
2022	—	`conf`	Logical Fallacy Detection. EMNLP (Findings) Zhijing Jin, Abhinav Lalwani, Tejas Vaidhya, Xiaoyu Shen, Yiwen Ding, Zhiheng Lyu, Mrinmaya Sachan, Rada Mihalcea, Bernhard Schölkopf
2022	J	`jnl`	Logical Fallacy Detection. CoRR Zhijing Jin, Abhinav Lalwani, Tejas Vaidhya, Xiaoyu Shen, Yiwen Ding, Zhiheng Lyu, Mrinmaya Sachan, Rada Mihalcea, Bernhard Schölkopf
2022	—	`conf`	Maximum Mean Discrepancy Distributionally Robust Nonlinear Chance-Constrained Optimization with Finite-Sample Guarantee. CDC Yassine Nemmour, Heiner Kremer, Bernhard Schölkopf, Jia-Jie Zhu
2022	J	`jnl`	Maximum Mean Discrepancy Distributionally Robust Nonlinear Chance-Constrained Optimization with Finite-Sample Guarantee. CoRR Yassine Nemmour, Heiner Kremer, Bernhard Schölkopf, Jia-Jie Zhu
2022	A*	`conf`	Neural Attentive Circuits. NeurIPS Martin Weiss, Nasim Rahaman, Francesco Locatello, Chris Pal, Yoshua Bengio, Bernhard Schölkopf, Li Erran Li, Nicolas Ballas
2022	J	`jnl`	Neural Attentive Circuits. CoRR Nasim Rahaman, Martin Weiss, Francesco Locatello, Chris Pal, Yoshua Bengio, Bernhard Schölkopf, Li Erran Li, Nicolas Ballas
2022	J	`jnl`	Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference. CoRR Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
2022	J	`jnl`	On Pitfalls of Identifiability in Unsupervised Learning. A Note on: "Desiderata for Representation Learning: A Causal Perspective". CoRR Shubhangi Ghosh, Luigi Gresele, Julius von Kügelgen, Michel Besserve, Bernhard Schölkopf
2022	A*	`conf`	On the Adversarial Robustness of Causal Algorithmic Recourse. ICML Ricardo Dominguez-Olmedo, Amir-Hossein Karimi, Bernhard Schölkopf
2022	A*	`conf`	On the Fairness of Causal Algorithmic Recourse. AAAI Julius von Kügelgen, Amir-Hossein Karimi, Umang Bhatt, Isabel Valera, Adrian Weller, Bernhard Schölkopf
2022	J	`jnl`	On the Identifiability and Estimation of Causal Location-Scale Noise Models. CoRR Alexander Immer, Christoph Schultheiss, Julia E. Vogt, Bernhard Schölkopf, Peter Bühlmann, Alexander Marx
2022	J	`jnl`	On the Relationship Between Explanation and Prediction: A Causal View. CoRR Amir-Hossein Karimi, Krikamol Muandet, Simon Kornblith, Bernhard Schölkopf, Been Kim
2022	—	`conf`	Original or Translated? A Causal Analysis of the Impact of Translationese on Machine Translation Performance. NAACL-HLT Jingwei Ni, Zhijing Jin, Markus Freitag, Mrinmaya Sachan, Bernhard Schölkopf
2022	J	`jnl`	Original or Translated? A Causal Analysis of the Impact of Translationese on Machine Translation Performance. CoRR Jingwei Ni, Zhijing Jin, Markus Freitag, Mrinmaya Sachan, Bernhard Schölkopf
2022	A*	`conf`	Phenomenology of Double Descent in Finite-Width Neural Networks. ICLR Sidak Pal Singh, Aurélien Lucchi, Thomas Hofmann, Bernhard Schölkopf
2022	J	`jnl`	Phenomenology of Double Descent in Finite-Width Neural Networks. CoRR Sidak Pal Singh, Aurélien Lucchi, Thomas Hofmann, Bernhard Schölkopf
2022	J	`jnl`	Physical Derivatives: Computing policy gradients by physical forward-propagation. CoRR Arash Mehrjou, Ashkan Soleymani, Stefan Bauer, Bernhard Schölkopf
2022	A*	`conf`	Probable Domain Generalization via Quantile Risk Minimization. NeurIPS Cian Eastwood, Alexander Robey, Shashank Singh, Julius von Kügelgen, Hamed Hassani, George J. Pappas, Bernhard Schölkopf
2022	J	`jnl`	Probable Domain Generalization via Quantile Risk Minimization. CoRR Cian Eastwood, Alexander Robey, Shashank Singh, Julius von Kügelgen, Hamed Hassani, George J. Pappas, Bernhard Schölkopf
2022	J	`jnl`	Probing the Robustness of Independent Mechanism Analysis for Representation Learning. CoRR Joanna Sliwa, Shubhangi Ghosh, Vincent Stimper, Luigi Gresele, Bernhard Schölkopf
2022	J	`jnl`	Quantifying the Effects of Contact Tracing, Testing, and Containment Measures in the Presence of Infection Hotspots. ACM Trans. Spatial Algorithms Syst. Lars Lorch, Heiner Kremer, William Trouleau, Stratis Tsirtsis, Aron Szanto, Bernhard Schölkopf, Manuel Gomez-Rodriguez
2022	A	`conf`	Resampling Base Distributions of Normalizing Flows. AISTATS Vincent Stimper, Bernhard Schölkopf, José Miguel Hernández-Lobato
2022	A*	`conf`	Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization. NeurIPS Aniket Das, Bernhard Schölkopf, Michael Muehlebach
2022	J	`jnl`	Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization. CoRR Aniket Das, Bernhard Schölkopf, Michael Muehlebach
2022	A*	`conf`	Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models. ICML Paul Rolland, Volkan Cevher, Matthäus Kleindessner, Chris Russell, Dominik Janzing, Bernhard Schölkopf, Francesco Locatello
2022	J	`jnl`	Score matching enables causal discovery of nonlinear additive noise models. CoRR Paul Rolland, Volkan Cevher, Matthäus Kleindessner, Chris Russell, Bernhard Schölkopf, Dominik Janzing, Francesco Locatello
2022	A*	`conf`	Source-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration. ICLR Cian Eastwood, Ian Mason, Christopher K. I. Williams, Bernhard Schölkopf
2022	J	`jnl`	Spatial Context Awareness for Unsupervised Change Detection in Optical Satellite Images. IEEE Trans. Geosci. Remote. Sens. Lukas Kondmann, Aysim Toker, Sudipan Saha, Bernhard Schölkopf, Laura Leal-Taixé, Xiao Xiang Zhu
2022	J	`jnl`	Spectral Representation Learning for Conditional Moment Models. CoRR Ziyu Wang, Yucen Luo, Yueru Li, Jun Zhu, Bernhard Schölkopf
2022	—	`conf`	Structural Causal 3D Reconstruction. ECCV (1) Weiyang Liu, Zhen Liu, Liam Paull, Adrian Weller, Bernhard Schölkopf
2022	J	`jnl`	Structural Causal 3D Reconstruction. CoRR Weiyang Liu, Zhen Liu, Liam Paull, Adrian Weller, Bernhard Schölkopf
2022	A*	`conf`	The Role of Pretrained Representations for the OOD Generalization of RL Agents. ICLR Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
2022	A*	`conf`	Towards Principled Disentanglement for Domain Generalization. CVPR Hanlin Zhang, Yifan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing
2022	A*	`conf`	Towards Total Recall in Industrial Anomaly Detection. CVPR Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, Peter V. Gehler
2022	J	`jnl`	Understanding Stereotypes in Language Models: Towards Robust Measurement and Zero-Shot Debiasing. CoRR Justus Mattern, Zhijing Jin, Mrinmaya Sachan, Rada Mihalcea, Bernhard Schölkopf
2022	J	`jnl`	Variational Causal Dynamics: Discovering Modular World Models from Interventions. CoRR Anson Lei, Bernhard Schölkopf, Ingmar Posner
2022	A*	`conf`	Visual Representation Learning Does Not Generalize Strongly Within the Same Domain. ICLR Lukas Schott, Julius von Kügelgen, Frederik Träuble, Peter Vincent Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel
2022	A*	`conf`	When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment. NeurIPS Zhijing Jin, Sydney Levine, Fernando Gonzalez Adauto, Ojasv Kamal, Maarten Sap, Mrinmaya Sachan, Rada Mihalcea, Josh Tenenbaum, Bernhard Schölkopf
2022	J	`jnl`	When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment. CoRR Zhijing Jin, Sydney Levine, Fernando Gonzalez, Ojasv Kamal, Maarten Sap, Mrinmaya Sachan, Rada Mihalcea, Josh Tenenbaum, Bernhard Schölkopf
2022	A*	`conf`	You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction. ICLR Osama Makansi, Julius von Kügelgen, Francesco Locatello, Peter Vincent Gehler, Dominik Janzing, Thomas Brox, Bernhard Schölkopf
2021	J	`jnl`	A Robot Cluster for Reproducible Research in Dexterous Manipulation. CoRR Stefan Bauer, Felix Widmaier, Manuel Wüthrich, Niklas Funk, Julen Urain De Jesus, Jan Peters, Joe Watson, Claire Chen, Krishnan Srinivasan, Junwu Zhang, Jeffrey Zhang, Matthew R. Walter, Rishabh Madan, Charles B. Schaff, Takahiro Maeda, Takuma Yoneda, Denis Yarats, Arthur Allshire, Ethan K. Gordon, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa, Animesh Garg, Annika Buchholz, Sebastian Stark, Thomas Steinbrenner, Joel Akpo, Shruti Joshi, Vaibhav Agrawal, Bernhard Schölkopf
2021	A*	`conf`	A Theory of Independent Mechanisms for Extrapolation in Generative Models. AAAI Michel Besserve, Rémy Sun, Dominik Janzing, Bernhard Schölkopf
2021	J	`jnl`	A prior-based approximate latent Riemannian metric. CoRR Georgios Arvanitidis, Bogdan Georgiev, Bernhard Schölkopf
2021	A*	`conf`	A teacher-student framework to distill future trajectories. ICLR Alexander Neitz, Giambattista Parascandolo, Bernhard Schölkopf
2021	J	`jnl`	Action-Sufficient State Representation Learning for Control with Structural Constraints. CoRR Biwei Huang, Chaochao Lu, Liu Leqi, José Miguel Hernández-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang
2021	J	`jnl`	Adversarial Robustness through the Lens of Causality. CoRR Yonggang Zhang, Mingming Gong, Tongliang Liu, Gang Niu, Xinmei Tian, Bo Han, Bernhard Schölkopf, Kun Zhang
2021	J	`jnl`	Algorithmic Recourse in Partially and Fully Confounded Settings Through Bounding Counterfactual Effects. CoRR Julius von Kügelgen, Nikita Agarwal, Jakob Zeitler, Afsaneh Mastouri, Bernhard Schölkopf
2021	—	`conf`	Algorithmic Recourse: from Counterfactual Explanations to Interventions. FAccT Amir-Hossein Karimi, Bernhard Schölkopf, Isabel Valera
2021	J	`jnl`	An Optimal Witness Function for Two-Sample Testing. CoRR Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
2021	—	`conf`	Approximate Distributionally Robust Nonlinear Optimization with Application to Model Predictive Control: A Functional Approach. L4DC Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu
2021	J	`jnl`	ArmSym: A Virtual Human-Robot Interaction Laboratory for Assistive Robotics. IEEE Trans. Hum. Mach. Syst. Samuel Bustamante-Gomez, Jan Peters, Bernhard Schölkopf, Moritz Grosse-Wentrup, Vinay Jayaram
2021	A*	`conf`	Backward-Compatible Prediction Updates: A Probabilistic Approach. NeurIPS Frederik Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Peter V. Gehler
2021	J	`jnl`	Backward-Compatible Prediction Updates: A Probabilistic Approach. CoRR Frederik Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Peter V. Gehler
2021	A*	`conf`	Bayesian Quadrature on Riemannian Data Manifolds. ICML Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis
2021	J	`jnl`	Bayesian Quadrature on Riemannian Data Manifolds. CoRR Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis
2021	J	`jnl`	Boxhead: A Dataset for Learning Hierarchical Representations. CoRR Yukun Chen, Frederik Träuble, Andrea Dittadi, Stefan Bauer, Bernhard Schölkopf
2021	A*	`conf`	Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning. ICML Sumedh A. Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf
2021	—	`conf`	Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP. EMNLP (1) Zhijing Jin, Julius von Kügelgen, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan, Bernhard Schölkopf
2021	J	`jnl`	Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP. CoRR Zhijing Jin, Julius von Kügelgen, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan, Bernhard Schölkopf
2021	A*	`conf`	Causal Influence Detection for Improving Efficiency in Reinforcement Learning. NeurIPS Maximilian Seitzer, Bernhard Schölkopf, Georg Martius
2021	J	`jnl`	Causal Influence Detection for Improving Efficiency in Reinforcement Learning. CoRR Maximilian Seitzer, Bernhard Schölkopf, Georg Martius
2021	A*	`conf`	CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. ICLR Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wuthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer
2021	A*	`conf`	Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression. ICML Junhyung Park, Uri Shalit, Bernhard Schölkopf, Krikamol Muandet
2021	J	`jnl`	Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression. CoRR Junhyung Park, Uri Shalit, Bernhard Schölkopf, Krikamol Muandet
2021	A*	`conf`	DiBS: Differentiable Bayesian Structure Learning. NeurIPS Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause
2021	J	`jnl`	DiBS: Differentiable Bayesian Structure Learning. CoRR Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause
2021	J	`jnl`	Direct Advantage Estimation. CoRR Hsiao-Ru Pan, Nico Gürtler, Alexander Neitz, Bernhard Schölkopf
2021	J	`jnl`	Distributional Robustness Regularized Scenario Optimization with Application to Model Predictive Control. CoRR Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu
2021	A*	`conf`	Dynamic Inference with Neural Interpreters. NeurIPS Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter V. Gehler, Yoshua Bengio, Francesco Locatello, Bernhard Schölkopf
2021	J	`jnl`	Dynamic Inference with Neural Interpreters. CoRR Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter V. Gehler, Yoshua Bengio, Francesco Locatello, Bernhard Schölkopf
2021	A*	`conf`	Fast And Slow Learning Of Recurrent Independent Mechanisms. ICLR Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio
2021	J	`jnl`	Fast and Slow Learning of Recurrent Independent Mechanisms. CoRR Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio
2021	J	`jnl`	From Majorization to Interpolation: Distributionally Robust Learning using Kernel Smoothing. CoRR Jia-Jie Zhu, Yassine Nemmour, Bernhard Schölkopf
2021	A*	`conf`	Function Contrastive Learning of Transferable Meta-Representations. ICML Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wuthrich, Bernhard Schölkopf
2021	J	`jnl`	GalilAI: Out-of-Task Distribution Detection using Causal Active Experimentation for Safe Transfer RL. CoRR Sumedh A. Sontakke, Stephen Iota, Zizhao Hu, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf
2021	J	`jnl`	Generalization and Robustness Implications in Object-Centric Learning. CoRR Andrea Dittadi, Samuele Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello
2021	A	`conf`	Geometrically Enriched Latent Spaces. AISTATS Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf
2021	J	`jnl`	Group equivariant neural posterior estimation. CoRR Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Deistler, Bernhard Schölkopf, Jakob H. Macke
2021	A*	`conf`	Independent mechanism analysis, a new concept? NeurIPS Luigi Gresele, Julius von Kügelgen, Vincent Stimper, Bernhard Schölkopf, Michel Besserve
2021	J	`jnl`	Independent mechanism analysis, a new concept? CoRR Luigi Gresele, Julius von Kügelgen, Vincent Stimper, Bernhard Schölkopf, Michel Besserve
2021	J	`jnl`	Instrument Space Selection for Kernel Maximum Moment Restriction. CoRR Rui Zhang, Krikamol Muandet, Bernhard Schölkopf, Masaaki Imaizumi
2021	J	`jnl`	Interventional Assays for the Latent Space of Autoencoders. CoRR Felix Leeb, Stefan Bauer, Bernhard Schölkopf
2021	A*	`conf`	Iterative Teaching by Label Synthesis. NeurIPS Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller
2021	J	`jnl`	Iterative Teaching by Label Synthesis. CoRR Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller
2021	A	`conf`	Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation. AISTATS Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf
2021	J	`jnl`	Learning Neural Causal Models with Active Interventions. CoRR Nino Scherrer, Olexa Bilaniuk, Yashas Annadani, Anirudh Goyal, Patrick Schwab, Bernhard Schölkopf, Michael C. Mozer, Yoshua Bengio, Stefan Bauer, Nan Rosemary Ke
2021	A*	`conf`	Learning explanations that are hard to vary. ICLR Giambattista Parascandolo, Alexander Neitz, Antonio Orvieto, Luigi Gresele, Bernhard Schölkopf
2021	J	`jnl`	Learning soft interventions in complex equilibrium systems. CoRR Michel Besserve, Bernhard Schölkopf
2021	A	`conf`	Learning with Hyperspherical Uniformity. AISTATS Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller
2021	J	`jnl`	Learning with Hyperspherical Uniformity. CoRR Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller
2021	—	`conf`	Mining the Cause of Political Decision-Making from Social Media: A Case Study of COVID-19 Policies across the US States. EMNLP (Findings) Zhijing Jin, Zeyu Peng, Tejas Vaidhya, Bernhard Schölkopf, Rada Mihalcea
2021	J	`jnl`	Multi-Sided Matching Markets with Consistent Preferences and Cooperative Partners. CoRR Maximilian Mordig, Riccardo Della Vecchia, Nicolò Cesa-Bianchi, Bernhard Schölkopf
2021	A*	`conf`	Necessary and sufficient conditions for causal feature selection in time series with latent common causes. ICML Atalanti-Anastasia Mastakouri, Bernhard Schölkopf, Dominik Janzing
2021	—	`conf`	Neural Lyapunov Redesign. L4DC Arash Mehrjou, Mohammad Ghavamzadeh, Bernhard Schölkopf
2021	J	`jnl`	Nonlinear Invariant Risk Minimization: A Causal Approach. CoRR Chaochao Lu, Yuhuai Wu, José Miguel Hernández-Lobato, Bernhard Schölkopf
2021	A*	`conf`	On Disentangled Representations Learned from Correlated Data. ICML Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer
2021	J	`jnl`	On the Adversarial Robustness of Causal Algorithmic Recourse. CoRR Ricardo Dominguez-Olmedo, Amir-Hossein Karimi, Bernhard Schölkopf
2021	A*	`conf`	On the Transfer of Disentangled Representations in Realistic Settings. ICLR Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf
2021	A*	`conf`	Predicting Infectiousness for Proactive Contact Tracing. ICLR Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Benjamin Müller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David L. Buckeridge, Gaétan Marceau-Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Christopher J. Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams
2021	J	`jnl`	Pyfectious: An individual-level simulator to discover optimal containment polices for epidemic diseases. CoRR Arash Mehrjou, Ashkan Soleymani, Amin Abyaneh, Bernhard Schölkopf, Stefan Bauer
2021	—	`conf`	Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World. NeurIPS (Competition and Demos) Nico Gürtler, Felix Widmaier, Cansu Sancaktar, Sebastian Blaes, Pavel Kolev, Stefan Bauer, Manuel Wüthrich, Markus Wulfmeier, Martin A. Riedmiller, Arthur Allshire, Qiang Wang, Robert McCarthy, Hangyeol Kim, Jongchan Baek, Wookyong Kwon, Shanliang Qian, Yasunori Toshimitsu, Mike Yan Michelis, Amirhossein Kazemipour, Arman Raayatsanati, Hehui Zheng, Barnabas Gavin Cangan, Bernhard Schölkopf, Georg Martius
2021	—	`conf`	Real Robot Challenge: A Robotics Competition in the Cloud. NeurIPS (Competition and Demos) Stefan Bauer, Manuel Wüthrich, Felix Widmaier, Annika Buchholz, Sebastian Stark, Anirudh Goyal, Thomas Steinbrenner, Joel Akpo, Shruti Joshi, Vincent Berenz, Vaibhav Agrawal, Niklas Funk, Julen Urain De Jesus, Jan Peters, Joe Watson, Claire Chen, Krishnan Srinivasan, Junwu Zhang, Jeffrey Zhang, Matthew R. Walter, Rishabh Madan, Takuma Yoneda, Denis Yarats, Arthur Allshire, Ethan K. Gordon, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa, Animesh Garg, Takahiro Maeda, Harshit Sikchi, Jilong Wang, Qingfeng Yao, Shuyu Yang, Robert McCarthy, Francisco Roldan Sanchez, Qiang Wang, David Cordova Bulens, Kevin McGuinness, Noel E. O'Connor, Stephen J. Redmond, Bernhard Schölkopf
2021	J	`jnl`	Real-time gravitational-wave science with neural posterior estimation. CoRR Maximilian Dax, Stephen R. Green, Jonathan Gair, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
2021	A*	`conf`	Recurrent Independent Mechanisms. ICLR Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf
2021	A*	`conf`	Regret Bounds for Gaussian-Process Optimization in Large Domains. NeurIPS Manuel Wüthrich, Bernhard Schölkopf, Andreas Krause
2021	J	`jnl`	Regret Bounds for Gaussian-Process Optimization in Large Domains. CoRR Manuel Wüthrich, Bernhard Schölkopf, Andreas Krause
2021	J	`jnl`	Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning. CoRR Andrea Dittadi, Frederik Träuble, Manuel Wüthrich, Felix Widmaier, Peter V. Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
2021	J	`jnl`	Resampling Base Distributions of Normalizing Flows. CoRR Vincent Stimper, Bernhard Schölkopf, José Miguel Hernández-Lobato
2021	A*	`conf`	Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style. NeurIPS Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, Francesco Locatello
2021	J	`jnl`	Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style. CoRR Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, Francesco Locatello
2021	J	`jnl`	Shallow Representation is Deep: Learning Uncertainty-aware and Worst-case Random Feature Dynamics. CoRR Diego Agudelo-España, Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu
2021	J	`jnl`	Simpson's Paradox in COVID-19 Case Fatality Rates: A Mediation Analysis of Age-Related Causal Effects. IEEE Trans. Artif. Intell. Julius von Kügelgen, Luigi Gresele, Bernhard Schölkopf
2021	J	`jnl`	Source-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration. CoRR Cian Eastwood, Ian Mason, Christopher K. I. Williams, Bernhard Schölkopf
2021	J	`jnl`	Spatial Context Awareness for Unsupervised Change Detection in Optical Satellite Images. CoRR Lukas Kondmann, Aysim Toker, Sudipan Saha, Bernhard Schölkopf, Laura Leal-Taixé, Xiaoxiang Zhu
2021	A*	`conf`	Spatially Structured Recurrent Modules. ICLR Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf
2021	A*	`conf`	The Inductive Bias of Quantum Kernels. NeurIPS Jonas M. Kübler, Simon Buchholz, Bernhard Schölkopf
2021	J	`jnl`	Toward Causal Representation Learning. Proc. IEEE Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio
2021	J	`jnl`	Towards Causal Representation Learning. CoRR Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio
2021	J	`jnl`	Towards Principled Disentanglement for Domain Generalization. CoRR Hanlin Zhang, Yifan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing
2021	J	`jnl`	Towards Total Recall in Industrial Anomaly Detection. CoRR Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, Peter V. Gehler
2021	J	`jnl`	Uncertainty estimation and explainability in deep learning-based age estimation of the human brain: Results from the German National Cohort MRI study. Comput. Medical Imaging Graph. Tobias Hepp, Dominik Blum, Karim Armanious, Bernhard Schölkopf, Darko Stern, Bin Yang, Sergios Gatidis
2021	J	`jnl`	Unsupervised Object Learning via Common Fate. CoRR Matthias Tangemann, Steffen Schneider, Julius von Kügelgen, Francesco Locatello, Peter V. Gehler, Thomas Brox, Matthias Kümmerer, Matthias Bethge, Bernhard Schölkopf
2021	J	`jnl`	Visual Representation Learning Does Not Generalize Strongly Within the Same Domain. CoRR Lukas Schott, Julius von Kügelgen, Frederik Träuble, Peter V. Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel
2021	J	`jnl`	You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction. CoRR Osama Makansi, Julius von Kügelgen, Francesco Locatello, Peter V. Gehler, Dominik Janzing, Thomas Brox, Bernhard Schölkopf
2020	A*	`conf`	A Commentary on the Unsupervised Learning of Disentangled Representations. AAAI Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2020	J	`jnl`	A Commentary on the Unsupervised Learning of Disentangled Representations. CoRR Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2020	—	`conf`	A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control. L4DC Jia-Jie Zhu, Bernhard Schölkopf, Moritz Diehl
2020	J	`jnl`	A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control. CoRR Jia-Jie Zhu, Bernhard Schölkopf, Moritz Diehl
2020	A*	`conf`	A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models. ICRA Diego Agudelo-España, Andrii Zadaianchuk, Philippe Wenk, Aditya Garg, Joel Akpo, Felix Grimminger, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Georg Martius, Andreas Krause, Bernhard Schölkopf, Stefan Bauer, Manuel Wüthrich
2020	J	`jnl`	A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation. CoRR Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2020	J	`jnl`	A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation. J. Mach. Learn. Res. Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2020	J	`jnl`	A Spatiotemporal Epidemic Model to Quantify the Effects of Contact Tracing, Testing, and Containment. CoRR Lars Lorch, William Trouleau, Stratis Tsirtsis, Aron Szanto, Bernhard Schölkopf, Manuel Gomez-Rodriguez
2020	J	`jnl`	A survey of algorithmic recourse: definitions, formulations, solutions, and prospects. CoRR Amir-Hossein Karimi, Gilles Barthe, Bernhard Schölkopf, Isabel Valera
2020	J	`jnl`	A theory of independent mechanisms for extrapolation in generative models. CoRR Michel Besserve, Rémy Sun, Dominik Janzing, Bernhard Schölkopf
2020	J	`jnl`	Adaptation and Robust Learning of Probabilistic Movement Primitives. IEEE Trans. Robotics Sebastián Gómez-González, Gerhard Neumann, Bernhard Schölkopf, Jan Peters
2020	J	`jnl`	Algorithmic Recourse: from Counterfactual Explanations to Interventions. CoRR Amir-Hossein Karimi, Bernhard Schölkopf, Isabel Valera
2020	A*	`conf`	Algorithmic recourse under imperfect causal knowledge: a probabilistic approach. NeurIPS Amir-Hossein Karimi, Bodo Julius von Kügelgen, Bernhard Schölkopf, Isabel Valera
2020	J	`jnl`	Algorithmic recourse under imperfect causal knowledge: a probabilistic approach. CoRR Amir-Hossein Karimi, Julius von Kügelgen, Bernhard Schölkopf, Isabel Valera
2020	J	`jnl`	Automatic Policy Synthesis to Improve the Safety of Nonlinear Dynamical Systems. CoRR Arash Mehrjou, Mohammad Ghavamzadeh, Bernhard Schölkopf
2020	A	`conf`	Bayesian Online Prediction of Change Points. UAI Diego Agudelo-España, Sebastián Gómez-González, Stefan Bauer, Bernhard Schölkopf, Jan Peters
2020	J	`jnl`	Bloom Origami Assays: Practical Group Testing. CoRR Louis Abraham, Gary Bécigneul, Benjamin Coleman, Bernhard Schölkopf, Anshumali Shrivastava, Alexander J. Smola
2020	J	`jnl`	COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing. CoRR Prateek Gupta, Tegan Maharaj, Martin Weiss, Nasim Rahaman, Hannah Alsdurf, Abhinav Sharma, Nanor Minoyan, Soren Harnois-Leblanc, Victor Schmidt, Pierre-Luc St-Charles, Tristan Deleu, Andrew Williams, Akshay Patel, Meng Qu, Olexa Bilaniuk, Gaétan Marceau Caron, Pierre Luc Carrier, Satya Ortiz-Gagné, Marc-Andre Rousseau, David L. Buckeridge, Joumana Ghosn, Yang Zhang, Bernhard Schölkopf, Jian Tang, Irina Rish, Christopher Joseph Pal, Joanna Merckx, Eilif B. Müller, Yoshua Bengio
2020	J	`jnl`	Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning. CoRR Sumedh A. Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf
2020	J	`jnl`	Causal Discovery from Heterogeneous/Nonstationary Data. J. Mach. Learn. Res. Biwei Huang, Kun Zhang, Jiji Zhang, Joseph D. Ramsey, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schölkopf
2020	J	`jnl`	Causal Feature Selection via Orthogonal Search. CoRR Anant Raj, Stefan Bauer, Ashkan Soleymani, Michel Besserve, Bernhard Schölkopf
2020	A*	`conf`	Causal analysis of Covid-19 Spread in Germany. NeurIPS Atalanti-Anastasia Mastakouri, Bernhard Schölkopf
2020	J	`jnl`	CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. CoRR Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wüthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer
2020	A*	`conf`	Counterfactuals uncover the modular structure of deep generative models. ICLR Michel Besserve, Arash Mehrjou, Rémy Sun, Bernhard Schölkopf
2020	J	`jnl`	Crackovid: Optimizing Group Testing. CoRR Louis Abraham, Gary Bécigneul, Bernhard Schölkopf
2020	J	`jnl`	DeepMAsED: evaluating the quality of metagenomic assemblies. Bioinform. Olga Mineeva, Mateo Rojas-Carulla, Ruth E. Ley, Bernhard Schölkopf, Nicholas D. Youngblut
2020	A*	`conf`	Disentangling Factors of Variations Using Few Labels. ICLR Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem
2020	A	`conf`	Fair Decisions Despite Imperfect Predictions. AISTATS Niki Kilbertus, Manuel Gomez Rodriguez, Bernhard Schölkopf, Krikamol Muandet, Isabel Valera
2020	A*	`conf`	From Variational to Deterministic Autoencoders. ICLR Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari, Michael J. Black, Bernhard Schölkopf
2020	J	`jnl`	Function Contrastive Learning of Transferable Representations. CoRR Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wüthrich, Bernhard Schölkopf
2020	J	`jnl`	Geometrically Enriched Latent Spaces. CoRR Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf
2020	J	`jnl`	Is Independence all you need? On the Generalization of Representations Learned from Correlated Data. CoRR Frederik Träuble, Elliot Creager, Niki Kilbertus, Anirudh Goyal, Francesco Locatello, Bernhard Schölkopf, Stefan Bauer
2020	J	`jnl`	Kernel Distributionally Robust Optimization. CoRR Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf
2020	J	`jnl`	Learning Dynamical Systems using Local Stability Priors. CoRR Arash Mehrjou, Andrea Iannelli, Bernhard Schölkopf
2020	A*	`conf`	Learning Kernel Tests Without Data Splitting. NeurIPS Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
2020	J	`jnl`	Learning Kernel Tests Without Data Splitting. CoRR Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
2020	J	`jnl`	Learning explanations that are hard to vary. CoRR Giambattista Parascandolo, Alexander Neitz, Antonio Orvieto, Luigi Gresele, Bernhard Schölkopf
2020	J	`jnl`	Learning to Play Table Tennis From Scratch using Muscular Robots. CoRR Dieter Büchler, Simon Guist, Roberto Calandra, Vincent Berenz, Bernhard Schölkopf, Jan Peters
2020	A*	`conf`	MYND: Unsupervised Evaluation of Novel BCI Control Strategies on Consumer Hardware. UIST Matthias R. Hohmann, Lisa Konieczny, Michelle Hackl, Brian Wirth, Talha Zaman, Raffi Enficiaud, Moritz Grosse-Wentrup, Bernhard Schölkopf
2020	J	`jnl`	MYND: Unsupervised Evaluation of Novel BCI Control Strategies on Consumer Hardware. CoRR Matthias R. Hohmann, Lisa Konieczny, Michelle Hackl, Brian Wirth, Talha Zaman, Raffi Enficiaud, Moritz Grosse-Wentrup, Bernhard Schölkopf
2020	J	`jnl`	Maximum Moment Restriction for Instrumental Variable Regression. CoRR Rui Zhang, Masaaki Imaizumi, Bernhard Schölkopf, Krikamol Muandet
2020	A*	`conf`	ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. AAAI Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause, Stefan Bauer
2020	J	`jnl`	On the Fairness of Causal Algorithmic Recourse. CoRR Julius von Kügelgen, Umang Bhatt, Amir-Hossein Karimi, Isabel Valera, Adrian Weller, Bernhard Schölkopf
2020	J	`jnl`	On the Transfer of Disentangled Representations in Realistic Settings. CoRR Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wüthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf
2020	A	`conf`	On the design of consequential ranking algorithms. UAI Behzad Tabibian, Vicenç Gómez, Abir De, Bernhard Schölkopf, Manuel Gomez Rodriguez
2020	J	`jnl`	PanCast: Listening to Bluetooth Beacons for Epidemic Risk Mitigation. CoRR Gilles Barthe, Roberta De Viti, Peter Druschel, Deepak Garg, Manuel Gomez-Rodriguez, Pierfrancesco Ingo, Matthew Lentz, Aastha Mehta, Bernhard Schölkopf
2020	J	`jnl`	Physically constrained causal noise models for high-contrast imaging of exoplanets. CoRR Timothy D. Gebhard, Markus J. Bonse, Sascha P. Quanz, Bernhard Schölkopf
2020	J	`jnl`	Predicting Infectiousness for Proactive Contact Tracing. CoRR Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif B. Müller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David L. Buckeridge, Gaétan Marceau Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Chris Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams
2020	J	`jnl`	Real Time Trajectory Prediction Using Deep Conditional Generative Models. IEEE Robotics Autom. Lett. Sebastián Gómez-González, Sergey Prokudin, Bernhard Schölkopf, Jan Peters
2020	J	`jnl`	Real-time Prediction of COVID-19 related Mortality using Electronic Health Records. CoRR Patrick Schwab, Arash Mehrjou, Sonali Parbhoo, Leo Anthony Celi, Jürgen Hetzel, Markus Hofer, Bernhard Schölkopf, Stefan Bauer
2020	A*	`conf`	Relative gradient optimization of the Jacobian term in unsupervised deep learning. NeurIPS Luigi Gresele, Giancarlo Fissore, Adrián Javaloy, Bernhard Schölkopf, Aapo Hyvärinen
2020	J	`jnl`	Relative gradient optimization of the Jacobian term in unsupervised deep learning. CoRR Luigi Gresele, Giancarlo Fissore, Adrián Javaloy, Bernhard Schölkopf, Aapo Hyvärinen
2020	J	`jnl`	S2RMs: Spatially Structured Recurrent Modules. CoRR Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf
2020	J	`jnl`	SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives. CoRR Emmanouil Angelis, Philippe Wenk, Bernhard Schölkopf, Stefan Bauer, Andreas Krause
2020	J	`jnl`	Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation. CoRR Chaochao Lu, Biwei Huang, Ke Wang, José Miguel Hernández-Lobato, Kun Zhang, Bernhard Schölkopf
2020	A	`conf`	Semi-supervised learning, causality, and the conditional cluster assumption. UAI Julius von Kügelgen, Alexander Mey, Marco Loog, Bernhard Schölkopf
2020	J	`jnl`	Structural Autoencoders Improve Representations for Generation and Transfer. CoRR Felix Leeb, Yashas Annadani, Stefan Bauer, Bernhard Schölkopf
2020	A	`conf`	Testing Goodness of Fit of Conditional Density Models with Kernels. UAI Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf
2020	J	`jnl`	Testing Goodness of Fit of Conditional Density Models with Kernels. CoRR Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf
2020	—	`conf`	Towards Causal Algorithmic Recourse. xxAI@ICML Amir-Hossein Karimi, Julius von Kügelgen, Bernhard Schölkopf, Isabel Valera
2020	J	`jnl`	Towards causal generative scene models via competition of experts. CoRR Julius von Kügelgen, Ivan Ustyuzhaninov, Peter V. Gehler, Matthias Bethge, Bernhard Schölkopf
2020	Misc	`conf`	TriFinger: An Open-Source Robot for Learning Dexterity. CoRL Manuel Wuthrich, Felix Widmaier, Felix Grimminger, Shruti Joshi, Vaibhav Agrawal, Bilal Hammoud, Majid Khadiv, Miroslav Bogdanovic, Vincent Berenz, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Bernhard Schölkopf, Stefan Bauer
2020	J	`jnl`	TriFinger: An Open-Source Robot for Learning Dexterity. CoRR Manuel Wüthrich, Felix Widmaier, Felix Grimminger, Joel Akpo, Shruti Joshi, Vaibhav Agrawal, Bilal Hammoud, Majid Khadiv, Miroslav Bogdanovic, Vincent Berenz, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Bernhard Schölkopf, Stefan Bauer
2020	A*	`conf`	Weakly-Supervised Disentanglement Without Compromises. ICML Francesco Locatello, Ben Poole, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen
2020	J	`jnl`	Weakly-Supervised Disentanglement Without Compromises. CoRR Francesco Locatello, Ben Poole, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen
2020	—	`conf`	Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem. CDC Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf
2020	J	`jnl`	Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem. CoRR Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf
2019	J	`jnl`	A New Distribution-Free Concept for Representing, Comparing, and Propagating Uncertainty in Dynamical Systems with Kernel Probabilistic Programming. CoRR Jia-Jie Zhu, Krikamol Muandet, Moritz Diehl, Bernhard Schölkopf
2019	J	`jnl`	AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs. CoRR Gabriele Abbati, Philippe Wenk, Stefan Bauer, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf
2019	A*	`conf`	AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs. ICML Gabriele Abbati, Philippe Wenk, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf, Stefan Bauer
2019	J	`jnl`	Analysis of cause-effect inference by comparing regression errors. PeerJ Comput. Sci. Patrick Blöbaum, Dominik Janzing, Takashi Washio, Shohei Shimizu, Bernhard Schölkopf
2019	J	`jnl`	Bayesian Online Detection and Prediction of Change Points. CoRR Diego Agudelo-España, Sebastián Gómez-González, Stefan Bauer, Bernhard Schölkopf, Jan Peters
2019	—	`conf`	Beta Power May Meditate the Effect of Gamma-TACS on Motor Performance. EMBC Atalanti-Anastasia Mastakouri, Bernhard Schölkopf, Moritz Grosse-Wentrup
2019	J	`jnl`	Causal Discovery from Heterogeneous/Nonstationary Data. CoRR Biwei Huang, Kun Zhang, Jiji Zhang, Joseph D. Ramsey, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schölkopf
2019	J	`jnl`	Causality for Machine Learning. CoRR Bernhard Schölkopf
2019	—	`conf`	Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. RML@ICLR Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2019	A*	`conf`	Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. ICML Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2019	J	`jnl`	Consequential Ranking Algorithms and Long-term Welfare. CoRR Behzad Tabibian, Vicenç Gómez, Abir De, Bernhard Schölkopf, Manuel Gomez Rodriguez
2019	J	`jnl`	Convolutional neural networks: a magic bullet for gravitational-wave detection? CoRR Timothy D. Gebhard, Niki Kilbertus, Ian Harry, Bernhard Schölkopf
2019	A	`conf`	Coordinating Users of Shared Facilities via Data-driven Predictive Assistants and Game Theory. UAI Philipp Geiger, Michel Besserve, Justus Winkelmann, Claudius Proissl, Bernhard Schölkopf
2019	J	`jnl`	Data scarcity, robustness and extreme multi-label classification. Mach. Learn. Rohit Babbar, Bernhard Schölkopf
2019	—	`conf`	Disentangled State Space Models: Unsupervised Learning of dynamics across Heterogeneous Environments. DGS@ICLR Ðorðe Miladinovic, Muhammad Waleed Gondal, Bernhard Schölkopf, Joachim M. Buhmann, Stefan Bauer
2019	J	`jnl`	Disentangled State Space Representations. CoRR Ðorðe Miladinovic, Muhammad Waleed Gondal, Bernhard Schölkopf, Joachim M. Buhmann, Stefan Bauer
2019	J	`jnl`	Disentangling Factors of Variation Using Few Labels. CoRR Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem
2019	—	`conf`	Feature extraction from the Hermitian manifold for Brain-Computer Interfaces. NER Jiachen Xu, Vinay Jayaram, Bernhard Schölkopf, Moritz Grosse-Wentrup
2019	A*	`conf`	First-Order Adversarial Vulnerability of Neural Networks and Input Dimension. ICML Carl-Johann Simon-Gabriel, Yann Ollivier, Léon Bottou, Bernhard Schölkopf, David Lopez-Paz
2019	J	`jnl`	From Variational to Deterministic Autoencoders. CoRR Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari, Michael J. Black, Bernhard Schölkopf
2019	J	`jnl`	GeNet: Deep Representations for Metagenomics. CoRR Mateo Rojas-Carulla, Ilya O. Tolstikhin, Guillermo Luque, Nicholas D. Youngblut, Ruth E. Ley, Bernhard Schölkopf
2019	J	`jnl`	Improving Consequential Decision Making under Imperfect Predictions. CoRR Niki Kilbertus, Manuel Gomez-Rodriguez, Bernhard Schölkopf, Krikamol Muandet, Isabel Valera
2019	A*	`conf`	Kernel Mean Matching for Content Addressability of GANs. ICML Wittawat Jitkrittum, Patsorn Sangkloy, Muhammad Waleed Gondal, Amit Raj, James Hays, Bernhard Schölkopf
2019	J	`jnl`	Kernel Mean Matching for Content Addressability of GANs. CoRR Wittawat Jitkrittum, Patsorn Sangkloy, Muhammad Waleed Gondal, Amit Raj, James Hays, Bernhard Schölkopf
2019	A*	`conf`	Kernel Stein Tests for Multiple Model Comparison. NeurIPS Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum
2019	J	`jnl`	Kernel Stein Tests for Multiple Model Comparison. CoRR Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum
2019	—	`conf`	Learning causal mechanisms. GI-Jahrestagung Bernhard Schölkopf
2019	—	`conf`	MYND: A Platform for Large-scale Neuroscientific Studies. CHI Extended Abstracts Matthias R. Hohmann, Michelle Hackl, Brian Wirth, Talha Zaman, Raffi Enficiaud, Moritz Grosse-Wentrup, Bernhard Schölkopf
2019	J	`jnl`	Multidimensional Contrast Limited Adaptive Histogram Equalization. IEEE Access Vincent Stimper, Stefan Bauer, Ralph Ernstorfer, Bernhard Schölkopf, Rui Patrick Xian
2019	B	`conf`	Neural Signatures of Motor Skill in the Resting Brain. SMC Ozan Özdenizci, Timm Meyer, Felix A. Wichmann, Jan Peters, Bernhard Schölkopf, Müjdat Çetin, Moritz Grosse-Wentrup
2019	J	`jnl`	ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. CoRR Philippe Wenk, Gabriele Abbati, Stefan Bauer, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf
2019	A*	`conf`	On the Fairness of Disentangled Representations. NeurIPS Francesco Locatello, Gabriele Abbati, Thomas Rainforth, Stefan Bauer, Bernhard Schölkopf, Olivier Bachem
2019	J	`jnl`	On the Fairness of Disentangled Representations. CoRR Francesco Locatello, Gabriele Abbati, Tom Rainforth, Stefan Bauer, Bernhard Schölkopf, Olivier Bachem
2019	A*	`conf`	On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset. NeurIPS Muhammad Waleed Gondal, Manuel Wuthrich, Djordje Miladinovic, Francesco Locatello, Martin Breidt, Valentin Volchkov, Joel Akpo, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
2019	J	`jnl`	On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset. CoRR Muhammad Waleed Gondal, Manuel Wüthrich, Ðorðe Miladinovic, Francesco Locatello, Martin Breidt, Valentin Volchkov, Joel Akpo, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
2019	J	`jnl`	Optimal Decision Making Under Strategic Behavior. CoRR Moein Khajehnejad, Behzad Tabibian, Bernhard Schölkopf, Adish Singla, Manuel Gomez-Rodriguez
2019	J	`jnl`	Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks. CoRR Julius von Kügelgen, Paul K. Rubenstein, Bernhard Schölkopf, Adrian Weller
2019	A*	`conf`	Perceiving the arrow of time in autoregressive motion. NeurIPS Kristof Meding, Dominik Janzing, Bernhard Schölkopf, Felix A. Wichmann
2019	J	`jnl`	Quantum Mean Embedding of Probability Distributions. CoRR Jonas M. Kübler, Krikamol Muandet, Bernhard Schölkopf
2019	J	`jnl`	Real Time Trajectory Prediction Using Deep Conditional Generative Models. CoRR Sebastián Gómez-González, Sergey Prokudin, Bernhard Schölkopf, Jan Peters
2019	J	`jnl`	Recurrent Independent Mechanisms. CoRR Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf
2019	J	`jnl`	Reliable Real Time Ball Tracking for Robot Table Tennis. CoRR Sebastián Gómez-González, Yassine Nemmour, Bernhard Schölkopf, Jan Peters
2019	J	`jnl`	Reliable Real-Time Ball Tracking for Robot Table Tennis. Robotics Sebastián Gómez-González, Yassine Nemmour, Bernhard Schölkopf, Jan Peters
2019	J	`jnl`	Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise. J. Mach. Learn. Res. Niklas Pfister, Sebastian Weichwald, Peter Bühlmann, Bernhard Schölkopf
2019	A*	`conf`	Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness. ICML Raphael Suter, Ðorðe Miladinovic, Bernhard Schölkopf, Stefan Bauer
2019	A*	`conf`	Selecting causal brain features with a single conditional independence test per feature. NeurIPS Atalanti-Anastasia Mastakouri, Bernhard Schölkopf, Dominik Janzing
2019	J	`jnl`	Semi-Supervised Learning, Causality and the Conditional Cluster Assumption. CoRR Julius von Kügelgen, Marco Loog, Alexander Mey, Bernhard Schölkopf
2019	J	`jnl`	The Incomplete Rosetta Stone Problem: Identifiability Results for Multi-View Nonlinear ICA. CoRR Luigi Gresele, Paul K. Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schölkopf
2019	A	`conf`	The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA. UAI Luigi Gresele, Paul K. Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schölkopf
2019	J	`jnl`	Witnessing Adversarial Training in Reproducing Kernel Hilbert Spaces. CoRR Arash Mehrjou, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
2018	J	`jnl`	A Local Information Criterion for Dynamical Systems. CoRR Arash Mehrjou, Friedrich Solowjow, Sebastian Trimpe, Bernhard Schölkopf
2018	J	`jnl`	Adaptation and Robust Learning of Probabilistic Movement Primitives. CoRR Sebastián Gómez-González, Gerhard Neumann, Bernhard Schölkopf, Jan Peters
2018	A*	`conf`	Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models. NeurIPS Alexander Neitz, Giambattista Parascandolo, Stefan Bauer, Bernhard Schölkopf
2018	J	`jnl`	Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models. CoRR Alexander Neitz, Giambattista Parascandolo, Stefan Bauer, Bernhard Schölkopf
2018	J	`jnl`	Adversarial Extreme Multi-label Classification. CoRR Rohit Babbar, Bernhard Schölkopf
2018	J	`jnl`	Adversarial Vulnerability of Neural Networks Increases With Input Dimension. CoRR Carl-Johann Simon-Gabriel, Yann Ollivier, Bernhard Schölkopf, Léon Bottou, David Lopez-Paz
2018	J	`jnl`	Analysis of Cause-Effect Inference via Regression Errors. CoRR Patrick Blöbaum, Dominik Janzing, Takashi Washio, Shohei Shimizu, Bernhard Schölkopf
2018	J	`jnl`	Automatic Estimation of Modulation Transfer Functions. CoRR Matthias Bauer, Valentin Volchkov, Michael Hirsch, Bernhard Schölkopf
2018	B	`conf`	Automatic estimation of modulation transfer functions. ICCP Matthias Bauer, Valentin Volchkov, Michael Hirsch, Bernhard Schölkopf
2018	A	`conf`	Cause-Effect Inference by Comparing Regression Errors. AISTATS Patrick Blöbaum, Dominik Janzing, Takashi Washio, Shohei Shimizu, Bernhard Schölkopf
2018	J	`jnl`	Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. CoRR Francesco Locatello, Stefan Bauer, Mario Lucic, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2018	—	`conf`	Clustering Meets Implicit Generative Models. ICLR (Workshop) Francesco Locatello, Damien Vincent, Ilya O. Tolstikhin, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf
2018	J	`jnl`	Clustering Meets Implicit Generative Models. CoRR Francesco Locatello, Damien Vincent, Ilya O. Tolstikhin, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf
2018	J	`jnl`	Control of Musculoskeletal Systems Using Learned Dynamics Models. IEEE Robotics Autom. Lett. Dieter Buchler, Roberto Calandra, Bernhard Schölkopf, Jan Peters
2018	J	`jnl`	Coordination via predictive assistants from a game-theoretic view. CoRR Philipp Geiger, Justus Winkelmann, Claudius Proissl, Michel Besserve, Bernhard Schölkopf
2018	J	`jnl`	Counterfactuals uncover the modular structure of deep generative models. CoRR Michel Besserve, Rémy Sun, Bernhard Schölkopf
2018	J	`jnl`	Deconfounding Reinforcement Learning in Observational Settings. CoRR Chaochao Lu, Bernhard Schölkopf, José Miguel Hernández-Lobato
2018	J	`jnl`	Deep Energy Estimator Networks. CoRR Saeed Saremi, Arash Mehrjou, Bernhard Schölkopf, Aapo Hyvärinen
2018	J	`jnl`	Deep Nonlinear Non-Gaussian Filtering for Dynamical Systems. CoRR Arash Mehrjou, Bernhard Schölkopf
2018	A*	`conf`	Detecting non-causal artifacts in multivariate linear regression models. ICML Dominik Janzing, Bernhard Schölkopf
2018	J	`jnl`	Detecting non-causal artifacts in multivariate linear regression models. CoRR Dominik Janzing, Bernhard Schölkopf
2018	A*	`conf`	Differentially Private Database Release via Kernel Mean Embeddings. ICML Matej Balog, Ilya O. Tolstikhin, Bernhard Schölkopf
2018	J	`jnl`	Discriminative Transfer Learning for General Image Restoration. IEEE Trans. Image Process. Lei Xiao, Felix Heide, Wolfgang Heidrich, Bernhard Schölkopf, Michael Hirsch
2018	—	`conf`	Efficient Encoding of Dynamical Systems Through Local Approximations. CDC Friedrich Solowjow, Arash Mehrjou, Bernhard Schölkopf, Sebastian Trimpe
2018	—	`conf`	Fidelity-Weighted Learning. ICLR (Poster) Mostafa Dehghani, Arash Mehrjou, Stephan Gouws, Jaap Kamps, Bernhard Schölkopf
2018	A	`conf`	From Deterministic ODEs to Dynamic Structural Causal Models. UAI Paul K. Rubenstein, Stephan Bongers, Joris M. Mooij, Bernhard Schölkopf
2018	J	`jnl`	Generalization in anti-causal learning. CoRR Niki Kilbertus, Giambattista Parascandolo, Bernhard Schölkopf
2018	A*	`conf`	Generalized Score Functions for Causal Discovery. KDD Biwei Huang, Kun Zhang, Yizhu Lin, Bernhard Schölkopf, Clark Glymour
2018	A	`conf`	Group invariance principles for causal generative models. AISTATS Michel Besserve, Naji Shajarisales, Bernhard Schölkopf, Dominik Janzing
2018	A*	`conf`	Informative Features for Model Comparison. NeurIPS Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, Arthur Gretton
2018	J	`jnl`	Informative Features for Model Comparison. CoRR Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, Arthur Gretton
2018	J	`jnl`	Interventional Robustness of Deep Latent Variable Models. CoRR Raphael Suter, Ðorðe Miladinovic, Stefan Bauer, Bernhard Schölkopf
2018	J	`jnl`	Invariant Models for Causal Transfer Learning. J. Mach. Learn. Res. Mateo Rojas-Carulla, Bernhard Schölkopf, Richard E. Turner, Jonas Peters
2018	J	`jnl`	Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions. J. Mach. Learn. Res. Carl-Johann Simon-Gabriel, Bernhard Schölkopf
2018	—	`conf`	Learning Disentangled Representations with Wasserstein Auto-Encoders. ICLR (Workshop) Paul K. Rubenstein, Bernhard Schölkopf, Ilya O. Tolstikhin
2018	A*	`conf`	Learning Independent Causal Mechanisms. ICML Giambattista Parascandolo, Niki Kilbertus, Mateo Rojas-Carulla, Bernhard Schölkopf
2018	A	`conf`	Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation. WSDM Jooyeon Kim, Behzad Tabibian, Alice Oh, Bernhard Schölkopf, Manuel Gomez-Rodriguez
2018	J	`jnl`	Minimum Information Exchange in Distributed Systems. CoRR Friedrich Solowjow, Arash Mehrjou, Bernhard Schölkopf, Sebastian Trimpe
2018	A*	`conf`	On Matching Pursuit and Coordinate Descent. ICML Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy, Gunnar Rätsch, Bernhard Schölkopf, Sebastian U. Stich, Martin Jaggi
2018	J	`jnl`	On the Latent Space of Wasserstein Auto-Encoders. CoRR Paul K. Rubenstein, Bernhard Schölkopf, Ilya O. Tolstikhin
2018	J	`jnl`	Photorealistic Video Super Resolution. CoRR Eduardo Pérez-Pellitero, Mehdi S. M. Sajjadi, Michael Hirsch, Bernhard Schölkopf
2018	J	`jnl`	Revisiting First-Order Convex Optimization Over Linear Spaces. CoRR Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy, Gunnar Rätsch, Bernhard Schölkopf, Sebastian U. Stich, Martin Jaggi
2018	—	`conf`	Spatio-Temporal Transformer Network for Video Restoration. ECCV (3) Tae Hyun Kim, Mehdi S. M. Sajjadi, Michael Hirsch, Bernhard Schölkopf
2018	—	`conf`	Tempered Adversarial Networks. ICLR (Workshop) Mehdi S. M. Sajjadi, Giambattista Parascandolo, Arash Mehrjou, Bernhard Schölkopf
2018	A*	`conf`	Tempered Adversarial Networks. ICML Mehdi S. M. Sajjadi, Giambattista Parascandolo, Arash Mehrjou, Bernhard Schölkopf
2018	J	`jnl`	Tempered Adversarial Networks. CoRR Mehdi S. M. Sajjadi, Bernhard Schölkopf
2018	—	`conf`	The Unreasonable Effectiveness of Texture Transfer for Single Image Super-Resolution. ECCV Workshops (5) Muhammad Waleed Gondal, Bernhard Schölkopf, Michael Hirsch
2018	J	`jnl`	The Unreasonable Effectiveness of Texture Transfer for Single Image Super-resolution. CoRR Muhammad Waleed Gondal, Bernhard Schölkopf, Michael Hirsch
2018	—	`conf`	Wasserstein Auto-Encoders. ICLR Ilya O. Tolstikhin, Olivier Bousquet, Sylvain Gelly, Bernhard Schölkopf
2018	—	`conf`	Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders. ICLR (Workshop) Paul K. Rubenstein, Bernhard Schölkopf, Ilya O. Tolstikhin
2018	J	`jnl`	groupICA: Independent component analysis for grouped data. CoRR Niklas Pfister, Sebastian Weichwald, Peter Bühlmann, Bernhard Schölkopf
2017	—	`conf`	A Guided Task for Cognitive brain-Computer Interfaces. GBCIC Julia Moser, Matthias Hohmann, Bernhard Schölkopf, Moritz Grosse-Wentrup
2017	—	`conf`	AdaGAN: Boosting Generative Models. NIPS Ilya O. Tolstikhin, Sylvain Gelly, Olivier Bousquet, Carl-Johann Simon-Gabriel, Bernhard Schölkopf
2017	J	`jnl`	AdaGAN: Boosting Generative Models. CoRR Ilya O. Tolstikhin, Sylvain Gelly, Olivier Bousquet, Carl-Johann Simon-Gabriel, Bernhard Schölkopf
2017	J	`jnl`	Annealed Generative Adversarial Networks. CoRR Arash Mehrjou, Bernhard Schölkopf, Saeed Saremi
2017	J	`jnl`	Anticipatory action selection for human-robot table tennis. Artif. Intell. Zhikun Wang, Abdeslam Boularias, Katharina Mülling, Bernhard Schölkopf, Jan Peters
2017	—	`conf`	Avoiding Discrimination through Causal Reasoning. NIPS Niki Kilbertus, Mateo Rojas-Carulla, Giambattista Parascandolo, Moritz Hardt, Dominik Janzing, Bernhard Schölkopf
2017	J	`jnl`	Avoiding Discrimination through Causal Reasoning. CoRR Niki Kilbertus, Mateo Rojas-Carulla, Giambattista Parascandolo, Moritz Hardt, Dominik Janzing, Bernhard Schölkopf
2017	A*	`conf`	Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows. ICDM Biwei Huang, Kun Zhang, Jiji Zhang, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schölkopf
2017	J	`jnl`	BundleMAP: Anatomically localized classification, regression, and hypothesis testing in diffusion MRI. Pattern Recognit. Mohammad Khatami, Tobias Schmidt-Wilcke, Pia C. Sundgren, Amin Abbasloo, Bernhard Schölkopf, Thomas Schultz
2017	A	`conf`	Causal Consistency of Structural Equation Models. UAI Paul K. Rubenstein, Sebastian Weichwald, Stephan Bongers, Joris M. Mooij, Dominik Janzing, Moritz Grosse-Wentrup, Bernhard Schölkopf
2017	J	`jnl`	Causal Consistency of Structural Equation Models. CoRR Paul K. Rubenstein, Sebastian Weichwald, Stephan Bongers, Joris M. Mooij, Dominik Janzing, Moritz Grosse-Wentrup, Bernhard Schölkopf
2017	A*	`conf`	Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination. IJCAI Kun Zhang, Biwei Huang, Jiji Zhang, Clark Glymour, Bernhard Schölkopf
2017	A	`conf`	Causal Discovery from Temporally Aggregated Time Series. UAI Mingming Gong, Kun Zhang, Bernhard Schölkopf, Clark Glymour, Dacheng Tao
2017	—	`conf`	Closing One's eyes Affects amplitude modulation but not frequency modulation in a Cognitive BCI. GBCIC Marius Goerner, Bernhard Schölkopf, Moritz Grosse-Wentrup
2017	A	`conf`	DiSMEC: Distributed Sparse Machines for Extreme Multi-label Classification. WSDM Rohit Babbar, Bernhard Schölkopf
2017	A*	`conf`	Discovering Causal Signals in Images. CVPR David Lopez-Paz, Robert Nishihara, Soumith Chintala, Bernhard Schölkopf, Léon Bottou
2017	J	`jnl`	Discriminative Transfer Learning for General Image Restoration. CoRR Lei Xiao, Felix Heide, Wolfgang Heidrich, Bernhard Schölkopf, Michael Hirsch
2017	J	`jnl`	Discriminative k-shot learning using probabilistic models. CoRR Matthias Bauer, Mateo Rojas-Carulla, Jakub Bartlomiej Swiatkowski, Bernhard Schölkopf, Richard E. Turner
2017	A*	`conf`	Distilling Information Reliability and Source Trustworthiness from Digital Traces. WWW Behzad Tabibian, Isabel Valera, Mehrdad Farajtabar, Le Song, Bernhard Schölkopf, Manuel Gomez-Rodriguez
2017	A*	`conf`	EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis. ICCV Mehdi S. M. Sajjadi, Bernhard Schölkopf, Michael Hirsch
2017	J	`jnl`	Fidelity-Weighted Learning. CoRR Mostafa Dehghani, Arash Mehrjou, Stephan Gouws, Jaap Kamps, Bernhard Schölkopf
2017	A*	`conf`	Flexible Spatio-Temporal Networks for Video Prediction. CVPR Chaochao Lu, Michael Hirsch, Bernhard Schölkopf
2017	—	`conf`	Frequency peak features for low-channel classification in motor imagery paradigms. NER Vinay Jayaram, Bernhard Schölkopf, Moritz Grosse-Wentrup
2017	J	`jnl`	Group invariance principles for causal generative models. CoRR Michel Besserve, Naji Shajarisales, Bernhard Schölkopf, Dominik Janzing
2017	—	`conf`	Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning. NIPS Shixiang Gu, Tim Lillicrap, Richard E. Turner, Zoubin Ghahramani, Bernhard Schölkopf, Sergey Levine
2017	J	`jnl`	Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning. CoRR Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Bernhard Schölkopf, Sergey Levine
2017	J	`jnl`	Kernel Mean Embedding of Distributions: A Review and Beyond. Found. Trends Mach. Learn. Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf
2017	A*	`conf`	Learning Blind Motion Deblurring. ICCV Patrick Wieschollek, Michael Hirsch, Bernhard Schölkopf, Hendrik P. A. Lensch
2017	J	`jnl`	Learning Blind Motion Deblurring. CoRR Patrick Wieschollek, Michael Hirsch, Bernhard Schölkopf, Hendrik P. A. Lensch
2017	J	`jnl`	Learning Independent Causal Mechanisms. CoRR Giambattista Parascandolo, Mateo Rojas-Carulla, Niki Kilbertus, Bernhard Schölkopf
2017	J	`jnl`	Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation. CoRR Jooyeon Kim, Behzad Tabibian, Alice Oh, Bernhard Schölkopf, Manuel Gomez-Rodriguez
2017	A	`conf`	Local Group Invariant Representations via Orbit Embeddings. AISTATS Anant Raj, Abhishek Kumar, Youssef Mroueh, Tom Fletcher, Bernhard Schölkopf
2017	A*	`conf`	Online Video Deblurring via Dynamic Temporal Blending Network. ICCV Tae Hyun Kim, Kyoung Mu Lee, Bernhard Schölkopf, Michael Hirsch
2017	J	`jnl`	Online Video Deblurring via Dynamic Temporal Blending Network. CoRR Tae Hyun Kim, Kyoung Mu Lee, Bernhard Schölkopf, Michael Hirsch
2017	J	`jnl`	Optimizing Human Learning. CoRR Behzad Tabibian, Utkarsh Upadhyay, Abir De, Ali Zarezade, Bernhard Schölkopf, Manuel Gomez-Rodriguez
2017	J	`jnl`	Personalized Brain-Computer Interface Models for Motor Rehabilitation. CoRR Anastasia-Atalanti Mastakouri, Sebastian Weichwald, Ozan Özdenizci, Timm Meyer, Bernhard Schölkopf, Moritz Grosse-Wentrup
2017	B	`conf`	Personalized brain-computer interface models for motor rehabilitation. SMC Anastasia-Atalanti Mastakouri, Sebastian Weichwald, Ozan Özdenizci, Timm Meyer, Bernhard Schölkopf, Moritz Grosse-Wentrup
2017	J	`jnl`	Probabilistic Active Learning of Functions in Structural Causal Models. CoRR Paul K. Rubenstein, Ilya O. Tolstikhin, Philipp Hennig, Bernhard Schölkopf
2017	J	`jnl`	Wasserstein Auto-Encoders. CoRR Ilya O. Tolstikhin, Olivier Bousquet, Sylvain Gelly, Bernhard Schölkopf
2016	—	`conf`	Approximate dual control maintaining the value of information with an application to building control. ECC Edgar D. Klenske, Philipp Hennig, Bernhard Schölkopf, Melanie Nicole Zeilinger
2016	J	`jnl`	Causal models for debugging and control in cloud computing. CoRR Philipp Geiger, Lucian Carata, Bernhard Schölkopf
2016	—	`conf`	Consistent Kernel Mean Estimation for Functions of Random Variables. NIPS Carl-Johann Simon-Gabriel, Adam Scibior, Ilya O. Tolstikhin, Bernhard Schölkopf
2016	—	`conf`	Depth Estimation Through a Generative Model of Light Field Synthesis. GCPR Mehdi S. M. Sajjadi, Rolf Köhler, Bernhard Schölkopf, Michael Hirsch
2016	J	`jnl`	Depth Estimation Through a Generative Model of Light Field Synthesis. CoRR Mehdi S. M. Sajjadi, Rolf Köhler, Bernhard Schölkopf, Michael Hirsch
2016	J	`jnl`	DiSMEC - Distributed Sparse Machines for Extreme Multi-label Classification. CoRR Rohit Babbar, Bernhard Schölkopf
2016	J	`jnl`	Discovering Causal Signals in Images. CoRR David Lopez-Paz, Robert Nishihara, Soumith Chintala, Bernhard Schölkopf, Léon Bottou
2016	J	`jnl`	Distilling Information Reliability and Source Trustworthiness from Digital Traces. CoRR Behzad Tabibian, Isabel Valera, Mehrdad Farajtabar, Le Song, Bernhard Schölkopf, Manuel Gomez-Rodriguez
2016	J	`jnl`	Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks. J. Mach. Learn. Res. Joris M. Mooij, Jonas Peters, Dominik Janzing, Jakob Zscheischler, Bernhard Schölkopf
2016	A*	`conf`	Domain Adaptation with Conditional Transferable Components. ICML Mingming Gong, Kun Zhang, Tongliang Liu, Dacheng Tao, Clark Glymour, Bernhard Schölkopf
2016	—	`conf`	End-to-End Learning for Image Burst Deblurring. ACCV (4) Patrick Wieschollek, Bernhard Schölkopf, Hendrik P. A. Lensch, Michael Hirsch
2016	J	`jnl`	End-to-End Learning for Image Burst Deblurring. CoRR Patrick Wieschollek, Michael Hirsch, Hendrik P. A. Lensch, Bernhard Schölkopf
2016	J	`jnl`	EnhanceNet: Single Image Super-Resolution through Automated Texture Synthesis. CoRR Mehdi S. M. Sajjadi, Bernhard Schölkopf, Michael Hirsch
2016	J	`jnl`	Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-thresholding Algorithm. J. Mach. Learn. Res. Manuel Gomez-Rodriguez, Le Song, Hadi Daneshmand, Bernhard Schölkopf
2016	J	`jnl`	Experimental and causal view on information integration in autonomous agents. CoRR Philipp Geiger, Katja Hofmann, Bernhard Schölkopf
2016	J	`jnl`	From Deterministic ODEs to Dynamic Structural Causal Models. CoRR Paul K. Rubenstein, Stephan Bongers, Joris M. Mooij, Bernhard Schölkopf
2016	J	`jnl`	Gaussian Process-Based Predictive Control for Periodic Error Correction. IEEE Trans. Control. Syst. Technol. Edgar D. Klenske, Melanie Nicole Zeilinger, Bernhard Schölkopf, Philipp Hennig
2016	J	`jnl`	Identification of causal relations in neuroimaging data with latent confounders: An instrumental variable approach. NeuroImage Moritz Grosse-Wentrup, Dominik Janzing, Markus Siegel, Bernhard Schölkopf
2016	J	`jnl`	Influence Estimation and Maximization in Continuous-Time Diffusion Networks. ACM Trans. Inf. Syst. Manuel Gomez-Rodriguez, Le Song, Nan Du, Hongyuan Zha, Bernhard Schölkopf
2016	—	`conf`	Jointly learning trajectory generation and hitting point prediction in robot table tennis. Humanoids Yanlong Huang, Dieter Buchler, Okan Koc, Bernhard Schölkopf, Jan Peters
2016	J	`jnl`	Kernel Mean Embedding of Distributions: A Review and Beyonds. CoRR Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf
2016	J	`jnl`	Kernel Mean Shrinkage Estimators. J. Mach. Learn. Res. Krikamol Muandet, Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf
2016	J	`jnl`	Learning to Deblur. IEEE Trans. Pattern Anal. Mach. Intell. Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf
2016	J	`jnl`	Local Group Invariant Representations via Orbit Embeddings. CoRR Anant Raj, Abhishek Kumar, Youssef Mroueh, P. Thomas Fletcher, Bernhard Schölkopf
2016	—	`conf`	Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels. NIPS Ilya O. Tolstikhin, Bharath K. Sriperumbudur, Bernhard Schölkopf
2016	J	`jnl`	Modeling confounding by half-sibling regression. Proc. Natl. Acad. Sci. USA Bernhard Schölkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters
2016	J	`jnl`	New Directions for Learning with Kernels and Gaussian Processes (Dagstuhl Seminar 16481). Dagstuhl Reports Arthur Gretton, Philipp Hennig, Carl Edward Rasmussen, Bernhard Schölkopf
2016	J	`jnl`	On Estimation of Functional Causal Models: General Results and Application to the Post-Nonlinear Causal Model. ACM Trans. Intell. Syst. Technol. Kun Zhang, Zhikun Wang, Jiji Zhang, Bernhard Schölkopf
2016	A	`conf`	On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection. UAI Kun Zhang, Jiji Zhang, Biwei Huang, Bernhard Schölkopf, Clark Glymour
2016	J	`jnl`	Optimal Coding in Biological and Artificial Neural Networks. CoRR Sebastian Weichwald, Tatiana Fomina, Bernhard Schölkopf, Moritz Grosse-Wentrup
2016	J	`jnl`	Preface to the ACM TIST Special Issue on Causal Discovery and Inference. ACM Trans. Intell. Syst. Technol. Kun Zhang, Jiuyong Li, Elias Bareinboim, Bernhard Schölkopf, Judea Pearl
2016	—	`conf`	Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data. PRNI Sebastian Weichwald, Arthur Gretton, Bernhard Schölkopf, Moritz Grosse-Wentrup
2016	J	`jnl`	Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data. CoRR Sebastian Weichwald, Arthur Gretton, Bernhard Schölkopf, Moritz Grosse-Wentrup
2016	J	`jnl`	Screening Rules for Convex Problems. CoRR Anant Raj, Jakob Olbrich, Bernd Gärtner, Bernhard Schölkopf, Martin Jaggi
2016	J	`jnl`	Structural Causal Models: Cycles, Marginalizations, Exogenous Reparametrizations and Reductions. CoRR Stephan Bongers, Jonas Peters, Bernhard Schölkopf, Joris M. Mooij
2016	A	`conf`	TerseSVM : A Scalable Approach for Learning Compact Models in Large-scale Classification. SDM Rohit Babbar, Krikamol Muandet, Bernhard Schölkopf
2016	A*	`conf`	The Arrow of Time in Multivariate Time Series. ICML Stefan Bauer, Bernhard Schölkopf, Jonas Peters
2016	J	`jnl`	Transfer Learning in Brain-Computer Interfaces Abstract\uFFFDThe performance of brain-computer interfaces (BCIs) improves with the amount of avail. IEEE Comput. Intell. Mag. Vinay Jayaram, Morteza Alamgir, Yasemin Altun, Bernhard Schölkopf, Moritz Grosse-Wentrup
2016	A*	`conf`	Unifying distillation and privileged information. ICLR (Poster) David Lopez-Paz, Léon Bottou, Bernhard Schölkopf, Vladimir Vapnik
2016	—	`conf`	Using probabilistic movement primitives for striking movements. Humanoids Sebastián Gómez-González, Gerhard Neumann, Bernhard Schölkopf, Jan Peters
2015	B	`conf`	A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis. SMC Matthias R. Hohmann, Tatiana Fomina, Vinay Jayaram, Natalie Widmann, Christian Forster, Jennifer Muller vom Hagen, Matthis Synofzik, Bernhard Schölkopf, Ludger Schöls, Moritz Grosse-Wentrup
2015	J	`jnl`	Artificial intelligence: Learning to see and act. Nat. Bernhard Schölkopf
2015	—	`conf`	Brain-computer interfacing in amyotrophic lateral sclerosis: Implications of a resting-state EEG analysis. EMBC Vinay Jayaram, Natalie Widmann, Christian Forster, Tatiana Fomina, Matthias Hohmann, Jennifer Muller vom Hagen, Matthis Synofzik, Bernhard Schölkopf, Ludger Schöls, Moritz Grosse-Wentrup
2015	—	`conf`	BundleMAP: Anatomically Localized Features from dMRI for Detection of Disease. MLMI Mohammad Khatami, Tobias Schmidt-Wilcke, Pia C. Sundgren, Amin Abbasloo, Bernhard Schölkopf, Thomas Schultz
2015	A*	`conf`	Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components. ICML Philipp Geiger, Kun Zhang, Bernhard Schölkopf, Mingming Gong, Dominik Janzing
2015	J	`jnl`	Causal and anti-causal learning in pattern recognition for neuroimaging. CoRR Sebastian Weichwald, Bernhard Schölkopf, Tonio Ball, Moritz Grosse-Wentrup
2015	J	`jnl`	Causal interpretation rules for encoding and decoding models in neuroimaging. CoRR Sebastian Weichwald, Timm Meyer, Ozan Özdenizci, Bernhard Schölkopf, Tonio Ball, Moritz Grosse-Wentrup
2015	J	`jnl`	Causal interpretation rules for encoding and decoding models in neuroimaging. NeuroImage Sebastian Weichwald, Timm Meyer, Ozan Özdenizci, Bernhard Schölkopf, Tonio Ball, Moritz Grosse-Wentrup
2015	J	`jnl`	Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations. CoRR Bernhard Schölkopf, Krikamol Muandet, Kenji Fukumizu, Jonas Peters
2015	J	`jnl`	Computing functions of random variables via reproducing kernel Hilbert space representations. Stat. Comput. Bernhard Schölkopf, Krikamol Muandet, Kenji Fukumizu, Stefan Harmeling, Jonas Peters
2015	A*	`conf`	Discovering Temporal Causal Relations from Subsampled Data. ICML Mingming Gong, Kun Zhang, Bernhard Schölkopf, Dacheng Tao, Philipp Geiger
2015	J	`jnl`	Distinguishing Cause from Effect Based on Exogeneity. CoRR Kun Zhang, Jiji Zhang, Bernhard Schölkopf
2015	A*	`conf`	Identification of Time-Dependent Causal Model: A Gaussian Process Treatment. IJCAI Biwei Huang, Kun Zhang, Bernhard Schölkopf
2015	—	`conf`	Identification of the Default Mode Network with electroencephalography. EMBC Tatiana Fomina, Matthias Hohmann, Bernhard Schölkopf, Moritz Grosse-Wentrup
2015	A	`conf`	Inference of Cause and Effect with Unsupervised Inverse Regression. AISTATS Eleni Sgouritsa, Dominik Janzing, Philipp Hennig, Bernhard Schölkopf
2015	A	`conf`	Learning optimal striking points for a ping-pong playing robot. IROS Yanlong Huang, Bernhard Schölkopf, Jan Peters
2015	A*	`conf`	Multi-Source Domain Adaptation: A Causal View. AAAI Kun Zhang, Mingming Gong, Bernhard Schölkopf
2015	A*	`conf`	Removing systematic errors for exoplanet search via latent causes. ICML Bernhard Schölkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters
2015	J	`jnl`	Removing systematic errors for exoplanet search via latent causes. CoRR Bernhard Schölkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters
2015	—	`conf`	Retrospective Motion Correction of Magnitude-Input MR Images. MLMMI@ICML Alexander Loktyushin, Christian J. Schuler, Klaus Scheffler, Bernhard Schölkopf
2015	A*	`conf`	Self-Calibration of Optical Lenses. ICCV Michael Hirsch, Bernhard Schölkopf
2015	J	`jnl`	Semi-supervised interpolation in an anticausal learning scenario. J. Mach. Learn. Res. Dominik Janzing, Bernhard Schölkopf
2015	A*	`conf`	Telling cause from effect in deterministic linear dynamical systems. ICML Naji Shajarisales, Dominik Janzing, Bernhard Schölkopf, Michel Besserve
2015	J	`jnl`	Telling cause from effect in deterministic linear dynamical systems. CoRR Naji Shajarisales, Dominik Janzing, Bernhard Schölkopf, Michel Besserve
2015	J	`jnl`	Towards Robust and Specific Causal Discovery from fMRI. CoRR Kun Zhang, Biwei Huang, Bernhard Schölkopf, Michel Besserve, Masataka Watanabe, Dajiang Zhu
2015	A*	`conf`	Towards a Learning Theory of Cause-Effect Inference. ICML David Lopez-Paz, Krikamol Muandet, Bernhard Schölkopf, Ilya O. Tolstikhin
2015	J	`jnl`	Transfer Learning in Brain-Computer Interfaces. CoRR Vinay Jayaram, Morteza Alamgir, Yasemin Altun, Bernhard Schölkopf, Moritz Grosse-Wentrup
2014	A	`conf`	A Permutation-Based Kernel Conditional Independence Test. UAI Gary Doran, Krikamol Muandet, Kun Zhang, Bernhard Schölkopf
2014	J	`jnl`	Causal Discovery via Reproducing Kernel Hilbert Space Embeddings. Neural Comput. Zhitang Chen, Kun Zhang, Laiwan Chan, Bernhard Schölkopf
2014	—	`conf`	Causal and anti-causal learning in pattern recognition for neuroimaging. PRNI Sebastian Weichwald, Bernhard Schölkopf, Tonio Ball, Moritz Grosse-Wentrup
2014	J	`jnl`	Causal discovery with continuous additive noise models. J. Mach. Learn. Res. Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf
2014	A*	`conf`	Consistency of Causal Inference under the Additive Noise Model. ICML Samory Kpotufe, Eleni Sgouritsa, Dominik Janzing, Bernhard Schölkopf
2014	J	`jnl`	Cost-Sensitive Active Learning With Lookahead: Optimizing Field Surveys for Remote Sensing Data Classification. IEEE Trans. Geosci. Remote. Sens. Claudio Persello, Abdeslam Boularias, Michele Dalponte, Terje Gobakken, Erik Næsset, Bernhard Schölkopf
2014	—	`conf`	Decoding index finger position from EEG using random forests. CIP Sebastian Weichwald, Timm Meyer, Bernhard Schölkopf, Tonio Ball, Moritz Grosse-Wentrup
2014	J	`jnl`	Distinguishing cause from effect using observational data: methods and benchmarks. CoRR Joris M. Mooij, Jonas Peters, Dominik Janzing, Jakob Zscheischler, Bernhard Schölkopf
2014	A	`conf`	Estimating Causal Effects by Bounding Confounding. UAI Philipp Geiger, Dominik Janzing, Bernhard Schölkopf
2014	A*	`conf`	Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm. ICML Hadi Daneshmand, Manuel Gomez-Rodriguez, Le Song, Bernhard Schölkopf
2014	J	`jnl`	Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm. CoRR Hadi Daneshmand, Manuel Gomez-Rodriguez, Le Song, Bernhard Schölkopf
2014	J	`jnl`	From Ordinary Differential Equations to Structural Causal Models: the deterministic case. CoRR Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf
2014	A	`conf`	Inferring latent structures via information inequalities. UAI Rafael Chaves, Lukas Luft, Thiago O. Maciel, David Gross, Dominik Janzing, Bernhard Schölkopf
2014	A*	`conf`	Kernel Mean Estimation and Stein Effect. ICML Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
2014	—	`conf`	Kernel Mean Estimation via Spectral Filtering. NIPS Krikamol Muandet, Bharath K. Sriperumbudur, Bernhard Schölkopf
2014	J	`jnl`	Kernel Mean Shrinkage Estimators. CoRR Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
2014	J	`jnl`	Learning strategies in table tennis using inverse reinforcement learning. Biol. Cybern. Katharina Mülling, Abdeslam Boularias, Betty J. Mohler, Bernhard Schölkopf, Jan Peters
2014	J	`jnl`	Learning to Deblur. CoRR Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf
2014	—	`conf`	Mask-Specific Inpainting with Deep Neural Networks. GCPR Rolf Köhler, Christian J. Schuler, Bernhard Schölkopf, Stefan Harmeling
2014	J	`jnl`	One-Class Support Measure Machines for Group Anomaly Detection. CoRR Krikamol Muandet, Bernhard Schölkopf
2014	A*	`conf`	Open Problem: Finding Good Cascade Sampling Processes for the Network Inference Problem. COLT Manuel Gomez-Rodriguez, Le Song, Bernhard Schölkopf
2014	A	`conf`	Quantifying Information Overload in Social Media and Its Impact on Social Contagions. ICWSM Manuel Gomez-Rodriguez, Krishna P. Gummadi, Bernhard Schölkopf
2014	J	`jnl`	Quantifying Information Overload in Social Media and its Impact on Social Contagions. CoRR Manuel Gomez-Rodriguez, Krishna P. Gummadi, Bernhard Schölkopf
2014	A*	`conf`	Randomized Nonlinear Component Analysis. ICML David Lopez-Paz, Suvrit Sra, Alexander J. Smola, Zoubin Ghahramani, Bernhard Schölkopf
2014	J	`jnl`	Randomized Nonlinear Component Analysis. CoRR David Lopez-Paz, Suvrit Sra, Alexander J. Smola, Zoubin Ghahramani, Bernhard Schölkopf
2014	A*	`conf`	Seeing the Arrow of Time. CVPR Lyndsey C. Pickup, Zheng Pan, Donglai Wei, Yi-Chang Shih, Changshui Zhang, Andrew Zisserman, Bernhard Schölkopf, William T. Freeman
2014	A	`conf`	Towards building a Crowd-Sourced Sky Map. AISTATS Dustin Lang, David W. Hogg, Bernhard Schölkopf
2014	J	`jnl`	Towards building a Crowd-Sourced Sky Map. CoRR Dustin Lang, David W. Hogg, Bernhard Schölkopf
2014	J	`jnl`	Uncovering the structure and temporal dynamics of information propagation. Netw. Sci. Manuel Gomez-Rodriguez, Jure Leskovec, David Balduzzi, Bernhard Schölkopf
2013	A*	`conf`	A Machine Learning Approach for Non-blind Image Deconvolution. CVPR Christian J. Schuler, Harold Christopher Burger, Stefan Harmeling, Bernhard Schölkopf
2013	—	`conf`	Causal Inference on Time Series using Restricted Structural Equation Models. NIPS Jonas Peters, Dominik Janzing, Bernhard Schölkopf
2013	J	`jnl`	Consistency of Causal Inference under the Additive Noise Model. CoRR Samory Kpotufe, Eleni Sgouritsa, Dominik Janzing, Bernhard Schölkopf
2013	—	`conf`	Domain Adaptation under Target and Conditional Shift. ICML (3) Kun Zhang, Bernhard Schölkopf, Krikamol Muandet, Zhikun Wang
2013	J	`jnl`	Domain Generalization via Invariant Feature Representation CoRR Krikamol Muandet, David Balduzzi, Bernhard Schölkopf
2013	—	`conf`	Domain Generalization via Invariant Feature Representation. ICML (1) Krikamol Muandet, David Balduzzi, Bernhard Schölkopf
2013	—	`ed.`	Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik Empirical Inference Bernhard Schölkopf, Zhiyuan Luo, Vladimir Vovk
2013	J	`jnl`	From Ordinary Differential Equations to Structural Causal Models: the deterministic case CoRR Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf
2013	A	`conf`	From Ordinary Differential Equations to Structural Causal Models: the deterministic case. UAI Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf
2013	J	`jnl`	HiFiVE: A Hilbert Space Embedding of Fiber Variability Estimates for Uncertainty Modeling and Visualization. Comput. Graph. Forum Thomas Schultz, Lara Schlaffke, Bernhard Schölkopf, Tobias Schmidt-Wilcke
2013	—	`conf`	How to Test the Quality of Reconstructed Sources in Independent Component Analysis (ICA) of EEG/MEG Data. PRNI Moritz Grosse-Wentrup, Stefan Harmeling, Thorsten O. Zander, N. Jeremy Hill, Bernhard Schölkopf
2013	A	`conf`	Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders. UAI Eleni Sgouritsa, Dominik Janzing, Jonas Peters, Bernhard Schölkopf
2013	J	`jnl`	Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders. CoRR Eleni Sgouritsa, Dominik Janzing, Jonas Peters, Bernhard Schölkopf
2013	B	`conf`	Improving alpha matting and motion blurred foreground estimation. ICIP Rolf Köhler, Michael Hirsch, Bernhard Schölkopf, Stefan Harmeling
2013	J	`jnl`	Kernel Mean Estimation and Stein's Effect. CoRR Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
2013	J	`jnl`	Modeling Information Propagation with Survival Theory CoRR Manuel Gomez-Rodriguez, Jure Leskovec, Bernhard Schölkopf
2013	—	`conf`	Modeling Information Propagation with Survival Theory. ICML (3) Manuel Gomez-Rodriguez, Jure Leskovec, Bernhard Schölkopf
2013	—	`conf`	Nonparametric dynamics estimation for time periodic systems. Allerton Edgar D. Klenske, Melanie Nicole Zeilinger, Bernhard Schölkopf, Philipp Hennig
2013	—	`conf`	On Estimation of Functional Causal Models: Post-Nonlinear Causal Model as an Example. ICDM Workshops Kun Zhang, Zhikun Wang, Bernhard Schölkopf
2013	A*	`conf`	On a Link Between Kernel Mean Maps and Fraunhofer Diffraction, with an Application to Super-Resolution Beyond the Diffraction Limit. CVPR Stefan Harmeling, Michael Hirsch, Bernhard Schölkopf
2013	—	`conf`	On the Relations and Differences Between Popper Dimension, Exclusion Dimension and VC-Dimension. Empirical Inference Yevgeny Seldin, Bernhard Schölkopf
2013	J	`jnl`	One-Class Support Measure Machines for Group Anomaly Detection CoRR Krikamol Muandet, Bernhard Schölkopf
2013	A	`conf`	One-Class Support Measure Machines for Group Anomaly Detection. UAI Krikamol Muandet, Bernhard Schölkopf
2013	J	`jnl`	Probabilistic movement modeling for intention inference in human-robot interaction. Int. J. Robotics Res. Zhikun Wang, Katharina Mülling, Marc Peter Deisenroth, Heni Ben Amor, David Vogt, Bernhard Schölkopf, Jan Peters
2013	J	`jnl`	Semi-Supervised Domain Adaptation with Non-Parametric Copulas CoRR David Lopez-Paz, José Miguel Hernández-Lobato, Bernhard Schölkopf
2013	—	`conf`	Semi-supervised Learning in Causal and Anticausal Settings. Empirical Inference Bernhard Schölkopf, Dominik Janzing, Jonas Peters, Eleni Sgouritsa, Kun Zhang, Joris M. Mooij
2013	—	`conf`	Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators. NIPS Michel Besserve, Nikos K. Logothetis, Bernhard Schölkopf
2013	A	`conf`	Structure and dynamics of information pathways in online media. WSDM Manuel Gomez-Rodriguez, Jure Leskovec, Bernhard Schölkopf
2013	—	`conf`	The Randomized Dependence Coefficient. NIPS David López-Paz, Philipp Hennig, Bernhard Schölkopf
2012	J	`jnl`	A Kernel Two-Sample Test. J. Mach. Learn. Res. Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
2012	B	`conf`	A blind deconvolution approach for pseudo CT prediction from MR image pairs. ICIP Michael Hirsch, Matthias Hofmann, Frederic Mantlik, Bernd J. Pichler, Bernhard Schölkopf, Michael Habeck
2012	A	`conf`	A brain-robot interface for studying motor learning after stroke. IROS Timm Meyer, Jan Peters, Doris Brtz, Thorsten O. Zander, Bernhard Schölkopf, Surjo R. Soekadar, Moritz Grosse-Wentrup
2012	—	`conf`	Blind Correction of Optical Aberrations. ECCV (3) Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf
2012	J	`jnl`	Causal Inference on Time Series using Structural Equation Models CoRR Jonas Peters, Dominik Janzing, Bernhard Schölkopf
2012	J	`jnl`	Detecting low-complexity unobserved causes CoRR Dominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schölkopf
2012	J	`jnl`	Identifiability of Causal Graphs using Functional Models CoRR Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf
2012	J	`jnl`	Identifying confounders using additive noise models CoRR Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schölkopf
2012	J	`jnl`	Inferring deterministic causal relations CoRR Povilas Daniusis, Dominik Janzing, Joris M. Mooij, Jakob Zscheischler, Bastian Steudel, Kun Zhang, Bernhard Schölkopf
2012	J	`jnl`	Influence Maximization in Continuous Time Diffusion Networks CoRR Manuel Gomez-Rodriguez, Bernhard Schölkopf
2012	A*	`conf`	Influence Maximization in Continuous Time Diffusion Networks. ICML Manuel Gomez-Rodriguez, Bernhard Schölkopf
2012	J	`jnl`	Information-geometric approach to inferring causal directions. Artif. Intell. Dominik Janzing, Joris M. Mooij, Kun Zhang, Jan Lemeire, Jakob Zscheischler, Povilas Daniusis, Bastian Steudel, Bernhard Schölkopf
2012	J	`jnl`	Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery CoRR Kun Zhang, Bernhard Schölkopf, Dominik Janzing
2012	J	`jnl`	Kernel-based Conditional Independence Test and Application in Causal Discovery CoRR Kun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schölkopf
2012	J	`jnl`	Learning from Distributions via Support Measure Machines CoRR Krikamol Muandet, Bernhard Schölkopf, Kenji Fukumizu, Francesco Dinuzzo
2012	—	`conf`	Learning from Distributions via Support Measure Machines. NIPS Krikamol Muandet, Kenji Fukumizu, Francesco Dinuzzo, Bernhard Schölkopf
2012	A*	`conf`	On causal and anticausal learning. ICML Bernhard Schölkopf, Dominik Janzing, Jonas Peters, Eleni Sgouritsa, Kun Zhang, Joris M. Mooij
2012	—	`conf`	Probabilistic Modeling of Human Movements for Intention Inference. Robotics: Science and Systems Zhikun Wang, Marc Peter Deisenroth, Heni Ben Amor, David Vogt, Bernhard Schölkopf, Jan Peters
2012	—	`conf`	Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database. ECCV (7) Rolf Köhler, Michael Hirsch, Betty J. Mohler, Bernhard Schölkopf, Stefan Harmeling
2012	—	`conf`	Semi-Supervised Domain Adaptation with Non-Parametric Copulas. NIPS David López-Paz, José Miguel Hernández-Lobato, Bernhard Schölkopf
2012	J	`jnl`	Structure and Dynamics of Information Pathways in Online Media CoRR Manuel Gomez-Rodriguez, Jure Leskovec, Bernhard Schölkopf
2012	J	`jnl`	Submodular Inference of Diffusion Networks from Multiple Trees CoRR Manuel Gomez-Rodriguez, Bernhard Schölkopf
2012	A*	`conf`	Submodular Inference of Diffusion Networks from Multiple Trees. ICML Manuel Gomez-Rodriguez, Bernhard Schölkopf
2012	J	`jnl`	The representer theorem for Hilbert spaces: a necessary and sufficient condition CoRR Francesco Dinuzzo, Bernhard Schölkopf
2012	—	`conf`	The representer theorem for Hilbert spaces: a necessary and sufficient condition. NIPS Francesco Dinuzzo, Bernhard Schölkopf
2012	J	`jnl`	easyGWAS: An integrated interspecies platform for performing genome-wide association studies CoRR Dominik G. Grimm, Bastian Greshake, Stefan Kleeberger, Christoph Lippert, Oliver Stegle, Bernhard Schölkopf, Detlef Weigel, Karsten M. Borgwardt
2011	J	`jnl`	A Blind Deconvolution Approach for Improving the Resolution of Cryo-EM Density Maps. J. Comput. Biol. Michael Hirsch, Bernhard Schölkopf, Michael Habeck
2011	J	`jnl`	A Graphical Model Framework for Decoding in the Visual ERP-Based BCI Speller. Neural Comput. Suzanna Martens, Joris M. Mooij, N. Jeremy Hill, Jason Farquhar, Bernhard Schölkopf
2011	J	`jnl`	Causal Inference on Discrete Data Using Additive Noise Models. IEEE Trans. Pattern Anal. Mach. Intell. Jonas Peters, Dominik Janzing, Bernhard Schölkopf
2011	J	`jnl`	Causal influence of gamma oscillations on the sensorimotor rhythm. NeuroImage Moritz Grosse-Wentrup, Bernhard Schölkopf, N. Jeremy Hill
2011	A	`conf`	Detecting low-complexity unobserved causes. UAI Dominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schölkopf
2011	A*	`conf`	Fast removal of non-uniform camera shake. ICCV Michael Hirsch, Christian J. Schuler, Stefan Harmeling, Bernhard Schölkopf
2011	Misc	`conf`	Finding dependencies between frequencies with the kernel cross-spectral density. ICASSP Michel Besserve, Dominik Janzing, Nikos K. Logothetis, Bernhard Schölkopf
2011	—	`book`	Handbook of Statistical Bioinformatics. Henry Horng-Shing Lu, Bernhard Schölkopf, Hongyu Zhao
2011	A	`conf`	Identifiability of Causal Graphs using Functional Models. UAI Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf
2011	A	`conf`	Kernel-based Conditional Independence Test and Application in Causal Discovery. UAI Kun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schölkopf
2011	A	`conf`	Learning anticipation policies for robot table tennis. IROS Zhikun Wang, Christoph H. Lampert, Katharina Mülling, Bernhard Schölkopf, Jan Peters
2011	A	`conf`	Learning inverse kinematics with structured prediction. IROS Botond Bocsi, Duy Nguyen-Tuong, Lehel Csató, Bernhard Schölkopf, Jan Peters
2011	J	`jnl`	Multi-way set enumeration in weight tensors. Mach. Learn. Elisabeth Georgii, Koji Tsuda, Bernhard Schölkopf
2011	A*	`conf`	Non-stationary correction of optical aberrations. ICCV Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf
2011	—	`conf`	On Causal Discovery with Cyclic Additive Noise Models. NIPS Joris M. Mooij, Dominik Janzing, Tom Heskes, Bernhard Schölkopf
2011	—	`conf`	Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance. NIPS Peter V. Gehler, Carsten Rother, Martin Kiefel, Lumin Zhang, Bernhard Schölkopf
2011	B	`conf`	Removing noise from astronomical images using a pixel-specific noise model. ICCP Harold Christopher Burger, Bernhard Schölkopf, Stefan Harmeling
2011	J	`jnl`	Robust Learning via Cause-Effect Models CoRR Bernhard Schölkopf, Dominik Janzing, Jonas Peters, Kun Zhang
2011	—	`ch.`	Statistical Learning Theory: Models, Concepts, and Results. Inductive Logic Ulrike von Luxburg, Bernhard Schölkopf
2011	A*	`conf`	Support Vector Machines as Probabilistic Models. ICML Vojtech Franc, Alexander Zien, Bernhard Schölkopf
2011	A*	`conf`	Two-locus association mapping in subquadratic time. KDD Panagiotis Achlioptas, Bernhard Schölkopf, Karsten M. Borgwardt
2011	J	`jnl`	Uncovering the Temporal Dynamics of Diffusion Networks CoRR Manuel Gomez-Rodriguez, David Balduzzi, Bernhard Schölkopf
2011	A*	`conf`	Uncovering the Temporal Dynamics of Diffusion Networks. ICML Manuel Gomez-Rodriguez, David Balduzzi, Bernhard Schölkopf
2010	B	`conf`	A New Algorithm for Improving the Resolution of Cryo-EM Density Maps. RECOMB Michael Hirsch, Bernhard Schölkopf, Michael Habeck
2010	A*	`conf`	Causal Markov Condition for Submodular Information Measures. COLT Bastian Steudel, Dominik Janzing, Bernhard Schölkopf
2010	J	`jnl`	Causal Markov condition for submodular information measures CoRR Bastian Steudel, Dominik Janzing, Bernhard Schölkopf
2010	J	`jnl`	Causal inference using the algorithmic Markov condition. IEEE Trans. Inf. Theory Dominik Janzing, Bernhard Schölkopf
2010	J	`jnl`	Causal relationships between frequency bands of extracellular signals in visual cortex revealed by an information theoretic analysis. J. Comput. Neurosci. Michel Besserve, Bernhard Schölkopf, Nikos K. Logothetis, Stefano Panzeri
2010	—	`ed.`	Causality: Objectives and Assessment (NIPS 2008 Workshop), Whistler, Canada, December 12, 2008 NIPS Causality: Objectives and Assessment Isabelle Guyon, Dominik Janzing, Bernhard Schölkopf
2010	—	`conf`	Causality: Objectives and Assessment. NIPS Causality: Objectives and Assessment Isabelle Guyon, Dominik Janzing, Bernhard Schölkopf
2010	B	`conf`	Closing the sensorimotor loop: Haptic feedback facilitates decoding of arm movement imagery. SMC Manuel Gomez-Rodriguez, Jan Peters, N. Jeremy Hill, Bernhard Schölkopf, Alireza Gharabaghi, Moritz Grosse-Wentrup
2010	A*	`conf`	Efficient filter flow for space-variant multiframe blind deconvolution. CVPR Michael Hirsch, Suvrit Sra, Bernhard Schölkopf, Stefan Harmeling
2010	J	`jnl`	Hilbert Space Embeddings and Metrics on Probability Measures. J. Mach. Learn. Res. Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, Gert R. G. Lanckriet
2010	A	`conf`	Identifying Cause and Effect on Discrete Data using Additive Noise Models. AISTATS Jonas Peters, Dominik Janzing, Bernhard Schölkopf
2010	A	`conf`	Inferring deterministic causal relations. UAI Povilas Daniusis, Dominik Janzing, Joris M. Mooij, Jakob Zscheischler, Bastian Steudel, Kun Zhang, Bernhard Schölkopf
2010	A	`conf`	Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery. UAI Kun Zhang, Bernhard Schölkopf, Dominik Janzing
2010	A*	`conf`	Movement templates for learning of hitting and batting. ICRA Jens Kober, Katharina Mülling, Oliver Kroemer, Christoph H. Lampert, Bernhard Schölkopf, Jan Peters
2010	B	`conf`	Multiframe blind deconvolution, super-resolution, and saturation correction via incremental EM. ICIP Stefan Harmeling, Suvrit Sra, Michael Hirsch, Bernhard Schölkopf
2010	B	`conf`	Non-parametric estimation of integral probability metrics. ISIT Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf, Gert R. G. Lanckriet
2010	J	`jnl`	Nonparametric Regression between General Riemannian Manifolds. SIAM J. Imaging Sci. Florian Steinke, Matthias Hein, Bernhard Schölkopf
2010	—	`conf`	Probabilistic latent variable models for distinguishing between cause and effect. NIPS Joris M. Mooij, Oliver Stegle, Dominik Janzing, Kun Zhang, Bernhard Schölkopf
2010	J	`jnl`	Remote Sensing Feature Selection by Kernel Dependence Measures. IEEE Geosci. Remote. Sens. Lett. Gustavo Camps-Valls, Joris M. Mooij, Bernhard Schölkopf
2010	—	`conf`	Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake. NIPS Stefan Harmeling, Michael Hirsch, Bernhard Schölkopf
2010	—	`conf`	Switched Latent Force Models for Movement Segmentation. NIPS Mauricio A. Álvarez, Jan Peters, Bernhard Schölkopf, Neil D. Lawrence
2010	A*	`conf`	Telling cause from effect based on high-dimensional observations. ICML Dominik Janzing, Patrik O. Hoyer, Bernhard Schölkopf
2010	—	`conf`	The Influence of the Image Basis on Modeling and Steganalysis Performance. Information Hiding Valentin Schwamberger, Pham Hai Dang Le, Bernhard Schölkopf, Matthias O. Franz
2009	—	`conf`	09401 Abstracts Collection - Machine learning approaches to statistical dependences and causality. Machine learning approaches to statistical dependences and causality Dominik Janzing, Steffen L. Lauritzen, Bernhard Schölkopf
2009	J	`jnl`	A note on integral probability metrics and $\phi$-divergences CoRR Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf
2009	A*	`conf`	Detecting the direction of causal time series. ICML Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schölkopf
2009	Misc	`conf`	Generalized Clustering via Kernel Embeddings. KI Stefanie Jegelka, Arthur Gretton, Bernhard Schölkopf, Bharath K. Sriperumbudur, Ulrike von Luxburg
2009	A	`conf`	Identifying confounders using additive noise models. UAI Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schölkopf
2009	—	`conf`	Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions. NIPS Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Gert R. G. Lanckriet, Bernhard Schölkopf
2009	A*	`conf`	Learning similarity measure for multi-modal 3D image registration. CVPR Daewon Lee, Matthias Hofmann, Florian Steinke, Yasemin Altun, Nathan D. Cahill, Bernhard Schölkopf
2009	—	`ed.`	Machine learning approaches to statistical dependences and causality, 27.09. - 02.10.2009 Machine learning approaches to statistical dependences and causality Dominik Janzing, Steffen L. Lauritzen, Bernhard Schölkopf
2009	—	`conf`	Markerless 3D Face Tracking. DAGM-Symposium Christian Walder, Martin Breidt, Heinrich H. Bülthoff, Bernhard Schölkopf, Cristóbal Curio
2009	—	`conf`	Multi-way set enumeration in real-valued tensors. KDD Workshop on Data Mining using Matrices and Tensors Elisabeth Georgii, Koji Tsuda, Bernhard Schölkopf
2009	J	`jnl`	Protein functional class prediction with a combined graph. Expert Syst. Appl. Hyunjung Shin, Koji Tsuda, Bernhard Schölkopf
2009	J	`jnl`	Prototype Classification: Insights from Machine Learning. Neural Comput. Arnulf B. A. Graf, Olivier Bousquet, Gunnar Rätsch, Bernhard Schölkopf
2009	A*	`conf`	Regression by dependence minimization and its application to causal inference in additive noise models. ICML Joris M. Mooij, Dominik Janzing, Jonas Peters, Bernhard Schölkopf
2009	A	`conf`	Sparse online model learning for robot control with support vector regression. IROS Duy Nguyen-Tuong, Bernhard Schölkopf, Jan Peters
2008	J	`jnl`	A Kernel Method for the Two-Sample Problem CoRR Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
2008	—	`conf`	An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis. NIPS Gabriele Beate Schweikert, Christian Widmer, Bernhard Schölkopf, Gunnar Rätsch
2008	B	`conf`	Automatic 3D face reconstruction from single images or video. FG Pia Breuer, Kwang In Kim, Wolf Kienzle, Bernhard Schölkopf, Volker Blanz
2008	—	`conf`	Automatic Image Colorization Via Multimodal Predictions. ECCV (3) Guillaume Charpiat, Matthias Hofmann, Bernhard Schölkopf
2008	—	`conf`	Bayesian Experimental Design of Magnetic Resonance Imaging Sequences. NIPS Matthias W. Seeger, Hannes Nickisch, Rolf Pohmann, Bernhard Schölkopf
2008	J	`jnl`	Causal inference using the algorithmic Markov condition CoRR Dominik Janzing, Bernhard Schölkopf
2008	J	`jnl`	Causal reasoning by evaluating the complexity of conditional densities with kernel methods. Neurocomputing Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf
2008	—	`conf`	Characteristic Kernels on Groups and Semigroups. NIPS Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
2008	—	`conf`	Diffeomorphic Dimensionality Reduction. NIPS Christian Walder, Bernhard Schölkopf
2008	—	`conf`	Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance. NIPS N. Jeremy Hill, Jason Farquhar, Suzanna Martens, Felix Bießmann, Bernhard Schölkopf
2008	J	`jnl`	Guest Editorial. Int. J. Comput. Vis. William T. Freeman, Pietro Perona, Bernhard Schölkopf
2008	A*	`conf`	Injective Hilbert Space Embeddings of Probability Measures. COLT Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf
2008	—	`conf`	Kernel Methods for Detecting the Direction of Time Series. GfKl Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schölkopf
2008	J	`jnl`	Kernels, regularization and differential equations. Pattern Recognit. Florian Steinke, Bernhard Schölkopf
2008	B	`conf`	Learning Inverse Dynamics: a Comparison. ESANN Duy Nguyen-Tuong, Jan Peters, Matthias W. Seeger, Bernhard Schölkopf
2008	J	`jnl`	Manifold-valued Thin-Plate Splines with Applications in Computer Graphics. Comput. Graph. Forum Florian Steinke, Matthias Hein, Jan Peters, Bernhard Schölkopf
2008	—	`conf`	Nonlinear causal discovery with additive noise models. NIPS Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij, Jonas Peters, Bernhard Schölkopf
2008	A*	`conf`	Sparse multiscale gaussian process regression. ICML Christian Walder, Kwang In Kim, Bernhard Schölkopf
2008	J	`jnl`	Support Vector Machines and Kernels for Computational Biology. PLoS Comput. Biol. Asa Ben-Hur, Cheng Soon Ong, Sören Sonnenburg, Bernhard Schölkopf, Gunnar Rätsch
2008	A*	`conf`	Tailoring density estimation via reproducing kernel moment matching. ICML Le Song, Xinhua Zhang, Alexander J. Smola, Arthur Gretton, Bernhard Schölkopf
2007	B	`conf`	A Hilbert Space Embedding for Distributions. ALT Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf
2007	B	`conf`	A Hilbert Space Embedding for Distributions. Discovery Science Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf
2007	A*	`conf`	A Kernel Approach to Comparing Distributions. AAAI Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
2007	—	`conf`	A Kernel Statistical Test of Independence. NIPS Arthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, Alexander J. Smola
2007	A*	`conf`	A kernel-based causal learning algorithm. ICML Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf, Kenji Fukumizu
2007	—	`ed.`	Advances in Neural Information Processing Systems 19, Proceedings of the Twentieth Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 4-7, 2006 NIPS Bernhard Schölkopf, John C. Platt, Thomas Hofmann
2007	—	`conf`	An Analysis of Inference with the Universum. NIPS Fabian H. Sinz, Olivier Chapelle, Alekh Agarwal, Bernhard Schölkopf
2007	B	`conf`	Distinguishing between cause and effect via kernel-based complexity measures for conditional distributions. ESANN Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf
2007	J	`jnl`	Feature Selection for Troubleshooting in Complex Assembly Lines. IEEE Trans Autom. Sci. Eng. Tobias Pfingsten, Daniel J. L. Herrmann, Thomas Schnitzler, Andreas Feustel, Bernhard Schölkopf
2007	—	`conf`	How to Find Interesting Locations in Video: A Spatiotemporal Interest Point Detector Learned from Human Eye Movements. DAGM-Symposium Wolf Kienzle, Bernhard Schölkopf, Felix A. Wichmann, Matthias O. Franz
2007	J	`jnl`	Improving the PLoS Comput. Biol. Gunnar Rätsch, Sören Sonnenburg, Jagan Srinivasan, Hanh Witte, Klaus-Robert Müller, Ralf J. Sommer, Bernhard Schölkopf
2007	—	`conf`	Kernel Measures of Conditional Dependence. NIPS Kenji Fukumizu, Arthur Gretton, Xiaohai Sun, Bernhard Schölkopf
2007	A*	`conf`	Local learning projections. ICML Mingrui Wu, Kai Yu, Shipeng Yu, Bernhard Schölkopf
2007	J	`jnl`	Real-Time Fetal Heart Monitoring in Biomagnetic Measurements Using Adaptive Real-Time ICA. IEEE Trans. Biomed. Eng. Stephan Waldert, Michael Bensch, Martin Bogdan, Wolfgang Rosenstiel, Bernhard Schölkopf, Curtis L. Lowery, Hari Eswaran, Hubert Preissl
2007	J	`jnl`	The Need for Open Source Software in Machine Learning. J. Mach. Learn. Res. Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Pascal Vincent, Jason Weston, Robert C. Williamson
2007	—	`conf`	Towards Machine Learning of Motor Skills. AMS Jan Peters, Stefan Schaal, Bernhard Schölkopf
2007	A	`conf`	Transductive Classification via Local Learning Regularization. AISTATS Mingrui Wu, Bernhard Schölkopf
2006	J	`jnl`	A Direct Method for Building Sparse Kernel Learning Algorithms. J. Mach. Learn. Res. Mingrui Wu, Bernhard Schölkopf, Gökhan H. Bakir
2006	—	`ch.`	A Discussion of Semi-Supervised Learning and Transduction. Semi-Supervised Learning Olivier Chapelle, Bernhard Schölkopf, Alexander Zien
2006	—	`conf`	A Kernel Method for the Two-Sample-Problem. NIPS Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
2006	—	`conf`	A Local Learning Approach for Clustering. NIPS Mingrui Wu, Bernhard Schölkopf
2006	—	`conf`	A Nonparametric Approach to Bottom-Up Visual Saliency. NIPS Wolf Kienzle, Felix A. Wichmann, Bernhard Schölkopf, Matthias O. Franz
2006	J	`jnl`	A Unifying View of Wiener and Volterra Theory and Polynomial Kernel Regression. Neural Comput. Matthias O. Franz, Bernhard Schölkopf
2006	—	`ch.`	Analysis of Benchmarks. Semi-Supervised Learning Olivier Chapelle, Bernhard Schölkopf, Alexander Zien
2006	—	`conf`	Causal Inference by Choosing Graphs with Most Plausible Markov Kernels. AI&M Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf
2006	J	`jnl`	Classification of Faces in Man and Machine. Neural Comput. Arnulf B. A. Graf, Felix A. Wichmann, Heinrich H. Bülthoff, Bernhard Schölkopf
2006	—	`conf`	Classifying Event-Related Desynchronization in EEG, ECoG and MEG Signals. DAGM-Symposium N. Jeremy Hill, Thomas Navin Lal, Michael Schröder, Thilo Hinterberger, Guido Widman, Christian Erich Elger, Bernhard Schölkopf, Niels Birbaumer
2006	—	`ch.`	Combining a Filter Method with SVMs. Feature Extraction Thomas Navin Lal, Olivier Chapelle, Bernhard Schölkopf
2006	—	`conf`	Correcting Sample Selection Bias by Unlabeled Data. NIPS Jiayuan Huang, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Bernhard Schölkopf
2006	—	`ch.`	Discrete Regularization. Semi-Supervised Learning Dengyong Zhou, Bernhard Schölkopf
2006	J	`jnl`	Implicit Surface Modelling with a Globally Regularised Basis of Compact Support. Comput. Graph. Forum Christian Walder, Bernhard Schölkopf, Olivier Chapelle
2006	—	`conf`	Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions. NIPS Christian Walder, Bernhard Schölkopf, Olivier Chapelle
2006	—	`conf`	Integrating structured biological data by Kernel Maximum Mean Discrepancy. ISMB (Supplement of Bioinformatics) Karsten M. Borgwardt, Arthur Gretton, Malte J. Rasch, Hans-Peter Kriegel, Bernhard Schölkopf, Alexander J. Smola
2006	—	`ch.`	Introduction to Semi-Supervised Learning. Semi-Supervised Learning Olivier Chapelle, Bernhard Schölkopf, Alexander Zien
2006	J	`jnl`	Large Scale Multiple Kernel Learning. J. Mach. Learn. Res. Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer, Bernhard Schölkopf
2006	—	`conf`	Learning Dense 3D Correspondence. NIPS Florian Steinke, Bernhard Schölkopf, Volker Blanz
2006	—	`conf`	Learning an Interest Operator from Human Eye Movements. CVPR Workshops Wolf Kienzle, Felix A. Wichmann, Bernhard Schölkopf, Matthias O. Franz
2006	—	`conf`	Learning with Hypergraphs: Clustering, Classification, and Embedding. NIPS Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf
2006	—	`book`	Semi-Supervised Learning Olivier Chapelle, Bernhard Schölkopf, Alexander Zien
2005	A*	`conf`	A brain computer interface with online feedback based on magnetoencephalography. ICML Thomas Navin Lal, Michael Schröder, N. Jeremy Hill, Hubert Preißl, Thilo Hinterberger, Jürgen Mellinger, Martin Bogdan, Wolfgang Rosenstiel, Thomas Hofmann, Niels Birbaumer, Bernhard Schölkopf
2005	A*	`conf`	Building Sparse Large Margin Classifiers. ICML Mingrui Wu, Bernhard Schölkopf, Gökhan H. Bakir
2005	—	`conf`	Evaluating Predictive Uncertainty Challenge. MLCW Joaquin Quiñonero Candela, Carl Edward Rasmussen, Fabian H. Sinz, Olivier Bousquet, Bernhard Schölkopf
2005	J	`jnl`	Experimentally optimal nu in support vector regression for different noise models and parameter settings. Neural Networks Athanassia Chalimourda, Bernhard Schölkopf, Alexander J. Smola
2005	—	`conf`	Fast protein classification with multiple networks. ECCB/JBI Koji Tsuda, Hyunjung Shin, Bernhard Schölkopf
2005	A*	`conf`	Implicit surface modelling as an eigenvalue problem. ICML Christian Walder, Olivier Chapelle, Bernhard Schölkopf
2005	J	`jnl`	Iterative Kernel Principal Component Analysis for Image Modeling. IEEE Trans. Pattern Anal. Mach. Intell. Kwang In Kim, Matthias O. Franz, Bernhard Schölkopf
2005	Misc	`conf`	Joint Kernel Maps. IWANN Jason Weston, Bernhard Schölkopf, Olivier Bousquet
2005	A	`conf`	Kernel Constrained Covariance for Dependence Measurement. AISTATS Arthur Gretton, Alexander J. Smola, Olivier Bousquet, Ralf Herbrich, Andrei Belitski, Mark Augath, Yusuke Murayama, Jon Pauls, Bernhard Schölkopf, Nikos K. Logothetis
2005	J	`jnl`	Kernel Methods for Measuring Independence. J. Mach. Learn. Res. Arthur Gretton, Ralf Herbrich, Alexander J. Smola, Olivier Bousquet, Bernhard Schölkopf
2005	A*	`conf`	Large scale genomic sequence SVM classifiers. ICML Sören Sonnenburg, Gunnar Rätsch, Bernhard Schölkopf
2005	A*	`conf`	Learning from labeled and unlabeled data on a directed graph. ICML Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf
2005	Misc	`conf`	Long Term Prediction of Product Quality in a Glass Manufacturing Process Using a Kernel Based Approach. IWANN Tobias Jung, Luis Javier Herrera, Bernhard Schölkopf
2005	J	`jnl`	Maximal margin classification for metric spaces. J. Comput. Syst. Sci. Matthias Hein, Olivier Bousquet, Bernhard Schölkopf
2005	B	`conf`	Measuring Statistical Dependence with Hilbert-Schmidt Norms. ALT Arthur Gretton, Olivier Bousquet, Alexander J. Smola, Bernhard Schölkopf
2005	A*	`conf`	Object correspondence as a machine learning problem. ICML Bernhard Schölkopf, Florian Steinke, Volker Blanz
2005	—	`conf`	RASE: recognition of alternatively spliced exons in ISMB (Supplement of Bioinformatics) Gunnar Rätsch, Sören Sonnenburg, Bernhard Schölkopf
2005	—	`conf`	Regularization on Discrete Spaces. DAGM-Symposium Dengyong Zhou, Bernhard Schölkopf
2005	J	`jnl`	Robust EEG Channel Selection across Subjects for Brain-Computer Interfaces. EURASIP J. Adv. Signal Process. Michael Schröder, Thomas Navin Lal, Thilo Hinterberger, Martin Bogdan, N. Jeremy Hill, Niels Birbaumer, Wolfgang Rosenstiel, Bernhard Schölkopf
2005	J	`jnl`	Support Vector Machines for 3D Shape Processing. Comput. Graph. Forum Florian Steinke, Bernhard Schölkopf, Volker Blanz
2005	—	`conf`	Training Support Vector Machines with Multiple Equality Constraints. ECML Wolf Kienzle, Bernhard Schölkopf
2004	J	`jnl`	A Compression Approach to Support Vector Model Selection. J. Mach. Learn. Res. Ulrike von Luxburg, Olivier Bousquet, Bernhard Schölkopf
2004	A*	`conf`	A kernel view of the dimensionality reduction of manifolds. ICML Jihun Ham, Daniel D. Lee, Sebastian Mika, Bernhard Schölkopf
2004	J	`jnl`	A tutorial on support vector regression. Stat. Comput. Alexander J. Smola, Bernhard Schölkopf
2004	—	`ed.`	Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, NIPS 2003, December 8-13, 2003, Vancouver and Whistler, British Columbia, Canada] NIPS Sebastian Thrun, Lawrence K. Saul, Bernhard Schölkopf
2004	—	`conf`	An Auditory Paradigm for Brain-Computer Interfaces. NIPS N. Jeremy Hill, Thomas Navin Lal, Karin Bierig, Niels Birbaumer, Bernhard Schölkopf
2004	—	`conf`	Efficient Approximations for Support Vector Machines in Object Detection. DAGM-Symposium Wolf Kienzle, Gökhan H. Bakir, Matthias O. Franz, Bernhard Schölkopf
2004	J	`jnl`	Experimentally optimal v in support vector regression for different noise models and parameter settings. Neural Networks Athanassia Chalimourda, Bernhard Schölkopf, Alexander J. Smola
2004	—	`conf`	Face Detection - Efficient and Rank Deficient. NIPS Wolf Kienzle, Gökhan H. Bakir, Matthias O. Franz, Bernhard Schölkopf
2004	J	`jnl`	Feature Selection for Support Vector Machines Using Genetic Algorithms. Int. J. Artif. Intell. Tools Holger Fröhlich, Olivier Chapelle, Bernhard Schölkopf
2004	—	`conf`	Implicit Wiener Series for Higher-Order Image Analysis. NIPS Matthias O. Franz, Bernhard Schölkopf
2004	—	`conf`	Kernel Methods for Implicit Surface Modeling. NIPS Bernhard Schölkopf, Joachim Giesen, Simon Spalinger
2004	—	`conf`	Learning from Labeled and Unlabeled Data Using Random Walks. DAGM-Symposium Dengyong Zhou, Bernhard Schölkopf
2004	—	`conf`	Machine Learning Applied to Perception: Decision Images for Gender Classification. NIPS Felix A. Wichmann, Arnulf B. A. Graf, Eero P. Simoncelli, Heinrich H. Bülthoff, Bernhard Schölkopf
2004	—	`conf`	Methods Towards Invasive Human Brain Computer Interfaces. NIPS Thomas Navin Lal, Thilo Hinterberger, Guido Widman, Michael Schröder, N. Jeremy Hill, Wolfgang Rosenstiel, Christian Erich Elger, Bernhard Schölkopf, Niels Birbaumer
2004	—	`conf`	Multivariate Regression via Stiefel Manifold Constraints. DAGM-Symposium Gökhan H. Bakir, Arthur Gretton, Matthias O. Franz, Bernhard Schölkopf
2004	—	`ed.`	Pattern Recognition, 26th DAGM Symposium, August 30 - September 1, 2004, Tübingen, Germany, Proceedings DAGM-Symposium Carl Edward Rasmussen, Heinrich H. Bülthoff, Bernhard Schölkopf, Martin A. Giese
2004	—	`conf`	Semi-supervised Kernel Regression Using Whitened Function Classes. DAGM-Symposium Matthias O. Franz, Younghee Kwon, Carl Edward Rasmussen, Bernhard Schölkopf
2004	—	`conf`	Semi-supervised Learning on Directed Graphs. NIPS Dengyong Zhou, Bernhard Schölkopf, Thomas Hofmann
2004	J	`jnl`	Support vector channel selection in BCI. IEEE Trans. Biomed. Eng. Thomas Navin Lal, Michael Schröder, Thilo Hinterberger, Jason Weston, Martin Bogdan, Niels Birbaumer, Bernhard Schölkopf
2003	A*	`ed.`	Computational Learning Theory and Kernel Machines, 16th Annual Conference on Computational Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003, Washington, DC, USA, August 24-27, 2003, Proceedings COLT Bernhard Schölkopf, Manfred K. Warmuth
2003	J	`jnl`	Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces. IEEE Trans. Pattern Anal. Mach. Intell. Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller
2003	B	`conf`	Feature Selection for Support Vector Machines by Means of Genetic Algorithms. ICTAI Holger Fröhlich, Olivier Chapelle, Bernhard Schölkopf
2003	J	`jnl`	Feature selection and transduction for prediction of molecular bioactivity for drug design. Bioinform. Jason Weston, Fernando Pérez-Cruz, Olivier Bousquet, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf
2003	—	`conf`	Learning to Find Pre-Images. NIPS Gökhan H. Bakir, Jason Weston, Bernhard Schölkopf
2003	—	`conf`	Learning with Local and Global Consistency. NIPS Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston, Bernhard Schölkopf
2003	—	`conf`	Prediction on Spike Data Using Kernel Algorithms. NIPS Jan Eichhorn, Andreas S. Tolias, Alexander Zien, Malte Kuss, Carl Edward Rasmussen, Jason Weston, Nikos K. Logothetis, Bernhard Schölkopf
2003	—	`conf`	Ranking on Data Manifolds. NIPS Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf
2003	J	`jnl`	Statistical learning theory, capacity, and complexity. Complex. Bernhard Schölkopf
2003	J	`jnl`	Use of the Zero-Norm with Linear Models and Kernel Methods. J. Mach. Learn. Res. Jason Weston, André Elisseeff, Bernhard Schölkopf, Michael E. Tipping
2002	—	`conf`	A Kernel Approach for Learning from Almost Orthogonal Patterns. PKDD Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble
2002	—	`conf`	A Kernel Approach for Learning from almost Orthogonal Patterns. ECML Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble
2002	—	`conf`	A Short Introduction to Learning with Kernels. Machine Learning Summer School Bernhard Schölkopf, Alexander J. Smola
2002	—	`conf`	Bayesian Kernel Methods. Machine Learning Summer School Alexander J. Smola, Bernhard Schölkopf
2002	—	`conf`	Cluster Kernels for Semi-Supervised Learning. NIPS Olivier Chapelle, Jason Weston, Bernhard Schölkopf
2002	J	`jnl`	Constructing Boosting Algorithms from SVMs: An Application to One-Class Classification. IEEE Trans. Pattern Anal. Mach. Intell. Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Klaus-Robert Müller
2002	—	`conf`	Kernel Dependency Estimation. NIPS Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik
2002	—	`book`	Learning with Kernels: support vector machines, regularization, optimization, and beyond. Bernhard Schölkopf, Alexander Johannes Smola
2002	J	`jnl`	Support Vector Machines and Kernel Methods: The New Generation of Learning Machines. AI Mag. Nello Cristianini, Bernhard Schölkopf
2002	J	`jnl`	Training Invariant Support Vector Machines. Mach. Learn. Dennis DeCoste, Bernhard Schölkopf
2001	—	`conf`	A Generalized Representer Theorem. COLT/EuroCOLT Bernhard Schölkopf, Ralf Herbrich, Alexander J. Smola
2001	A	`conf`	A Kernel Approach for Vector Quantization with Guaranteed Distortion Bounds. AISTATS Michael E. Tipping, Bernhard Schölkopf
2001	A	`conf`	An improved training algorithm for kernel Fisher discriminants. AISTATS Sebastian Mika, Alexander J. Smola, Bernhard Schölkopf
2001	J	`jnl`	An introduction to kernel-based learning algorithms. IEEE Trans. Neural Networks Klaus-Robert Müller, Sebastian Mika, Gunnar Rätsch, Koji Tsuda, Bernhard Schölkopf
2001	A*	`conf`	Computationally Efficient Face Detection. ICCV Sami Romdhani, Philip H. S. Torr, Bernhard Schölkopf, Andrew Blake
2001	A*	`conf`	Estimating a Kernel Fisher Discriminant in the Presence of Label Noise. ICML Neil D. Lawrence, Bernhard Schölkopf
2001	J	`jnl`	Estimating the Support of a High-Dimensional Distribution. Neural Comput. Bernhard Schölkopf, John C. Platt, John Shawe-Taylor, Alexander J. Smola, Robert C. Williamson
2001	J	`jnl`	Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators. IEEE Trans. Inf. Theory Robert C. Williamson, Alexander J. Smola, Bernhard Schölkopf
2001	—	`conf`	Incorporating Invariances in Non-Linear Support Vector Machines. NIPS Olivier Chapelle, Bernhard Schölkopf
2001	A*	`conf`	Kernel Machine Based Learning for Multi-View Face Detection and Pose Estimation. ICCV Stan Z. Li, QingDong Fu, Lie Gu, Bernhard Schölkopf, Yimin Cheng, HongJiang Zhang
2001	J	`jnl`	Regularized Principal Manifolds. J. Mach. Learn. Res. Alexander J. Smola, Sebastian Mika, Bernhard Schölkopf, Robert C. Williamson
2001	—	`conf`	Sampling Techniques for Kernel Methods. NIPS Dimitris Achlioptas, Frank McSherry, Bernhard Schölkopf
2001	—	`ch.`	Statistical Learning and Kernel Methods. Data Fusion and Perception Bernhard Schölkopf
2000	—	`conf`	Choosing in Support Vector Regression with Different Noise Models: Theory and Experiments. IJCNN (5) Athanassia Chalimourda, Bernhard Schölkopf, Alexander J. Smola
2000	J	`jnl`	Engineering support vector machine kernels that recognize translation initiation sites. Bioinform. Alexander Zien, Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Thomas Lengauer, Klaus-Robert Müller
2000	A*	`conf`	Entropy Numbers of Linear Function Classes. COLT Robert C. Williamson, Alexander J. Smola, Bernhard Schölkopf
2000	—	`conf`	Four-legged Walking Gait Control Using a Neuromorphic Chip Interfaced to a Support Vector Learning Algorithm. NIPS Susanne Still, Bernhard Schölkopf, Klaus Hepp, Rodney J. Douglas
2000	J	`jnl`	New Support Vector Algorithms. Neural Comput. Bernhard Schölkopf, Alexander J. Smola, Robert C. Williamson, Peter L. Bartlett
2000	B	`conf`	Robust Ensemble Learning for Data Mining. PAKDD Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Sebastian Mika, Takashi Onoda, Klaus-Robert Müller
2000	A*	`conf`	Sparse Greedy Matrix Approximation for Machine Learning. ICML Alexander J. Smola, Bernhard Schölkopf
2000	—	`conf`	Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra. NIPS Paul M. Hayton, Bernhard Schölkopf, Lionel Tarassenko, Paul Anuzis
2000	—	`conf`	The Kernel Trick for Distances. NIPS Bernhard Schölkopf
1999	—	`conf`	Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites. German Conference on Bioinformatics Alexander Zien, Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Christian Lemmen, Alexander J. Smola, Thomas Lengauer, Klaus-Robert Müller
1999	—	`conf`	Entropy Numbers, Operators and Support Vector Kernels. EuroCOLT Robert C. Williamson, Alexander J. Smola, Bernhard Schölkopf
1999	J	`jnl`	Input space versus feature space in kernel-based methods. IEEE Trans. Neural Networks Bernhard Schölkopf, Sebastian Mika, Christopher J. C. Burges, Phil Knirsch, Klaus-Robert Müller, Gunnar Rätsch, Alexander J. Smola
1999	—	`conf`	Invariant Feature Extraction and Classification in Kernel Spaces. NIPS Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller
1999	J	`jnl`	Lernen mit Kernen: Support-Vektor-Methoden zur Analyse hochdimensionaler Daten. Inform. Forsch. Entwickl. Bernhard Schölkopf, Klaus-Robert Müller, Alexander J. Smola
1999	—	`conf`	Regularized Principal Manifolds. EuroCOLT Alexander J. Smola, Robert C. Williamson, Sebastian Mika, Bernhard Schölkopf
1999	—	`conf`	Support Vector Method for Novelty Detection. NIPS Bernhard Schölkopf, Robert C. Williamson, Alexander J. Smola, John Shawe-Taylor, John C. Platt
1999	—	`conf`	The Entropy Regularization Information Criterion. NIPS Alexander J. Smola, John Shawe-Taylor, Bernhard Schölkopf, Robert C. Williamson
1999	—	`conf`	v-Arc: Ensemble Learning in the Presence of Outliers. NIPS Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller, Takashi Onoda, Sebastian Mika
1998	—	`conf`	Fast Approximation of Support Vector Kernel Expansions, and an Interpretation of Clustering as Approximation in Feature Spaces. DAGM-Symposium Bernhard Schölkopf, Alexander J. Smola, Phil Knirsch, Chris Burges
1998	—	`conf`	Kernel PCA and De-Noising in Feature Spaces. NIPS Sebastian Mika, Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller, Matthias Scholz, Gunnar Rätsch
1998	J	`jnl`	Learning View Graphs for Robot Navigation. Auton. Robots Matthias O. Franz, Bernhard Schölkopf, Hanspeter A. Mallot, Heinrich H. Bülthoff
1998	—	`conf`	Navigation mit Schnappschüssen. DAGM-Symposium Matthias O. Franz, Bernhard Schölkopf, Hanspeter A. Mallot, Heinrich H. Bülthoff, Andreas Zell
1998	J	`jnl`	Nonlinear Component Analysis as a Kernel Eigenvalue Problem. Neural Comput. Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller
1998	J	`jnl`	On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion. Algorithmica Alexander J. Smola, Bernhard Schölkopf
1998	—	`conf`	Semiparametric Support Vector and Linear Programming Machines. NIPS Alexander J. Smola, Thilo-Thomas Frieß, Bernhard Schölkopf
1998	—	`conf`	Shrinking the Tube: A New Support Vector Regression Algorithm. NIPS Bernhard Schölkopf, Peter L. Bartlett, Alexander J. Smola, Robert C. Williamson
1998	J	`jnl`	The connection between regularization operators and support vector kernels. Neural Networks Alexander J. Smola, Bernhard Schölkopf, Klaus-Robert Müller
1998	J	`jnl`	Where did I take that snapshot? Scene-based homing by image matching. Biol. Cybern. Matthias O. Franz, Bernhard Schölkopf, Hanspeter A. Mallot, Heinrich H. Bülthoff
1997	J	`jnl`	Comparing support vector machines with Gaussian kernels to radial basis function classifiers. IEEE Trans. Signal Process. Bernhard Schölkopf, Kah Kay Sung, Christopher J. C. Burges, Federico Girosi, Partha Niyogi, Tomaso A. Poggio, Vladimir Vapnik
1997	—	`conf`	From Regularization Operators to Support Vector Kernels. NIPS Alexander J. Smola, Bernhard Schölkopf
1997	C	`conf`	Kernel Principal Component Analysis. ICANN Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller
1997	—	`conf`	Learning View Graphs for Robot Navigation. Agents Matthias O. Franz, Bernhard Schölkopf, Philip Georg, Hanspeter A. Mallot, Heinrich H. Bülthoff
1997	C	`conf`	Predicting Time Series with Support Vector Machines. ICANN Klaus-Robert Müller, Alexander J. Smola, Gunnar Rätsch, Bernhard Schölkopf, Jens Kohlmorgen, Vladimir Vapnik
1997	—	`conf`	Prior Knowledge in Support Vector Kernels. NIPS Bernhard Schölkopf, Patrice Y. Simard, Alexander J. Smola, Vladimir Vapnik
1997	—	`—`	Support vector learning. Bernhard Schölkopf
1997	C	`conf`	The View-Graph Approach to Visual Navigation and Spatial Memory. ICANN Hanspeter A. Mallot, Matthias O. Franz, Bernhard Schölkopf, Heinrich H. Bülthoff
1996	C	`conf`	Comparison of View-Based Object Recognition Algorithms Using Realistic 3D Models. ICANN Volker Blanz, Bernhard Schölkopf, Heinrich H. Bülthoff, Chris Burges, Vladimir Vapnik, Thomas Vetter
1996	—	`conf`	Improving the Accuracy and Speed of Support Vector Machines. NIPS Christopher J. C. Burges, Bernhard Schölkopf
1996	C	`conf`	Incorporating Invariances in Support Vector Learning Machines. ICANN Bernhard Schölkopf, Chris Burges, Vladimir Vapnik
1995	A*	`conf`	Extracting Support Data for a Given Task. KDD Bernhard Schölkopf, Chris Burges, Vladimir Vapnik
1995	J	`jnl`	View-Based Cognitive Mapping and Path Planning. Adapt. Behav. Bernhard Schölkopf, Hanspeter A. Mallot