Max Welling - RankMe

461 papers A* 99A 46B 4C 2Misc 1Journal 239Unranked 60

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Categorical Flow Maps. CoRR Daan Roos, Oscar Davis, Floor Eijkelboom, Michael M. Bronstein, Max Welling, Ismail Ilkan Ceylan, Luca Ambrogioni, Jan-Willem van de Meent
2026	—	`book`	Equivariant and Coordinate Independent Convolutional Networks - A Gauge Field Theory of Neural Networks Equivariant and Coordinate Independent Convolutional Networks Maurice Weiler, Patrick Forré, Erik Verlinde, Max Welling
2026	J	`jnl`	Krause Synchronization Transformers. CoRR Jingkun Liu, Yisong Yue, Max Welling, Yue Song
2026	J	`jnl`	Private PoEtry: Private In-Context Learning via Product of Experts. CoRR Rob Romijnders, Mohammad Mahdi Derakhshani, Jonathan Petit, Max Welling, Christos Louizos, Yuki M. Asano
2026	J	`jnl`	Robust Stochastic Gradient Posterior Sampling with Lattice Based Discretisation. CoRR Zier Mensch, Lars Holdijk, Samuel Duffield, Maxwell Aifer, Patrick J. Coles, Max Welling, Miranda C. N. Cheng
2026	J	`jnl`	Unsupervised Representation Learning From Sparse Transformation Analysis. IEEE Trans. Pattern Anal. Mach. Intell. Yue Song, T. Anderson Keller, Yisong Yue, Pietro Perona, Max Welling
2025	J	`jnl`	A foundation model for the Earth system. Nat. Cristian Bodnar, Wessel P. Bruinsma, Ana Lucic, Megan Stanley, Anna Allen, Johannes Brandstetter, Patrick Garvan, Maik Riechert, Jonathan A. Weyn, Haiyu Dong, Jayesh K. Gupta, Kit Thambiratnam, Alexander T. Archibald, Chun-Chieh Wu, Elizabeth Heider, Max Welling, Richard E. Turner, Paris Perdikaris
2025	J	`jnl`	Accelerating scientific discovery with the common task framework. CoRR J. Nathan Kutz, Peter W. Battaglia, Michael P. Brenner, Kevin Carlberg, Aric A. Hagberg, Shirley Ho, Stephan Hoyer, Henning Lange, Hod Lipson, Michael W. Mahoney, Frank Noé, Max Welling, Laure Zanna, Francis Zhu, Steven L. Brunton
2025	J	`jnl`	Adaptive Mesh Quantization for Neural PDE Solvers. Trans. Mach. Learn. Res. Winfried van den Dool, Maksim Zhdanov, Yuki M. Asano, Max Welling
2025	J	`jnl`	Adaptive Mesh-Quantization for Neural PDE Solvers. CoRR Winfried van den Dool, Maksim Zhdanov, Yuki M. Asano, Max Welling
2025	A*	`conf`	Artificial Kuramoto Oscillatory Neurons. ICLR Takeru Miyato, Sindy Löwe, Andreas Geiger, Max Welling
2025	A*	`conf`	BARNN: A Bayesian Autoregressive and Recurrent Neural Network. ICML Dario Coscia, Max Welling, Nicola Demo, Gianluigi Rozza
2025	J	`jnl`	BARNN: A Bayesian Autoregressive and Recurrent Neural Network. CoRR Dario Coscia, Max Welling, Nicola Demo, Gianluigi Rozza
2025	J	`jnl`	BLIPs: Bayesian Learned Interatomic Potentials. CoRR Dario Coscia, Pim de Haan, Max Welling
2025	A*	`conf`	Controlled Generation with Equivariant Variational Flow Matching. ICML Floor Eijkelboom, Heiko Zimmermann, Sharvaree Vadgama, Erik J. Bekkers, Max Welling, Christian A. Naesseth, Jan-Willem van de Meent
2025	J	`jnl`	Controlled Generation with Equivariant Variational Flow Matching. CoRR Floor Eijkelboom, Heiko Zimmermann, Sharvaree Vadgama, Erik J. Bekkers, Max Welling, Christian A. Naesseth, Jan-Willem van de Meent
2025	A*	`conf`	Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems. ICML Maksim Zhdanov, Max Welling, Jan-Willem van de Meent
2025	J	`jnl`	Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems. CoRR Maksim Zhdanov, Max Welling, Jan-Willem van de Meent
2025	J	`jnl`	Kuramoto Orientation Diffusion Models. CoRR Yue Song, T. Anderson Keller, Sevan Brodjian, Takeru Miyato, Yisong Yue, Pietro Perona, Max Welling
2025	J	`jnl`	Langevin Flows for Modeling Neural Latent Dynamics. CoRR Yue Song, T. Anderson Keller, Yisong Yue, Pietro Perona, Max Welling
2025	J	`jnl`	Purrception: Variational Flow Matching for Vector-Quantized Image Generation. CoRR Razvan-Andrei Matisan, Vincent Tao Hu, Grigory Bartosh, Björn Ommer, Cees G. M. Snoek, Max Welling, Jan-Willem van de Meent, Mohammad Mahdi Derakhshani, Floor Eijkelboom
2024	J	`jnl`	A Spacetime Perspective on Dynamical Computation in Neural Information Processing Systems. CoRR T. Anderson Keller, Lyle Muller, Terrence J. Sejnowski, Max Welling
2024	J	`jnl`	Artificial Kuramoto Oscillatory Neurons. CoRR Takeru Miyato, Sindy Löwe, Andreas Geiger, Max Welling
2024	J	`jnl`	Aurora: A Foundation Model of the Atmosphere. CoRR Cristian Bodnar, Wessel P. Bruinsma, Ana Lucic, Megan Stanley, Johannes Brandstetter, Patrick Garvan, Maik Riechert, Jonathan A. Weyn, Haiyu Dong, Anna Vaughan, Jayesh K. Gupta, Kit Thambiratnam, Alexander T. Archibald, Elizabeth Heider, Max Welling, Richard E. Turner, Paris Perdikaris
2024	J	`jnl`	Binding Dynamics in Rotating Features. CoRR Sindy Löwe, Francesco Locatello, Max Welling
2024	J	`jnl`	DNA: Differentially private Neural Augmentation for contact tracing. CoRR Rob Romijnders, Christos Louizos, Yuki M. Asano, Max Welling
2024	J	`jnl`	Equivariant 3D-conditional diffusion model for molecular linker design. Nat. Mac. Intell. Ilia Igashov, Hannes Stärk, Clément Vignac, Arne Schneuing, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael M. Bronstein, Bruno E. Correia
2024	A*	`conf`	GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers. ICLR Takeru Miyato, Bernhard Jaeger, Max Welling, Andreas Geiger
2024	J	`jnl`	GUD: Generation with Unified Diffusion. CoRR Mathis Gerdes, Max Welling, Miranda C. N. Cheng
2024	J	`jnl`	Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI. CoRR Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
2024	A*	`conf`	Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. ICML Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
2024	A*	`conf`	Protect Your Score: Contact-Tracing with Differential Privacy Guarantees. AAAI Rob Romijnders, Christos Louizos, Yuki M. Asano, Max Welling
2024	J	`jnl`	Structure-based drug design with equivariant diffusion models. Nat. Comput. Sci. Arne Schneuing, Charles Harris, Yuanqi Du, Kieran Didi, Arian Rokkum Jamasb, Ilia Igashov, Weitao Du, Carla P. Gomes, Tom L. Blundell, Pietro Lio, Max Welling, Michael M. Bronstein, Bruno E. Correia
2024	A*	`conf`	Traveling Waves Encode The Recent Past and Enhance Sequence Learning. ICLR T. Anderson Keller, Lyle Muller, Terrence J. Sejnowski, Max Welling
2024	J	`jnl`	Unsupervised Representation Learning from Sparse Transformation Analysis. CoRR Yue Song, T. Anderson Keller, Yisong Yue, Pietro Perona, Max Welling
2024	A*	`conf`	Variational Flow Matching for Graph Generation. NeurIPS Floor Eijkelboom, Grigory Bartosh, Christian Andersson Naesseth, Max Welling, Jan-Willem van de Meent
2024	J	`jnl`	Variational Flow Matching for Graph Generation. CoRR Floor Eijkelboom, Grigory Bartosh, Christian Andersson Naesseth, Max Welling, Jan-Willem van de Meent
2023	A*	`conf`	Clifford Neural Layers for PDE Modeling. ICLR Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K. Gupta
2023	—	`conf`	Efficient Neural PDE-Solvers using Quantization Aware Training. ICCV (Workshops) Winfried van den Dool, Tijmen Blankevoort, Max Welling, Yuki M. Asano
2023	J	`jnl`	Efficient Neural PDE-Solvers using Quantization Aware Training. CoRR Winfried van den Dool, Tijmen Blankevoort, Max Welling, Yuki M. Asano
2023	A*	`conf`	Flow Factorized Representation Learning. NeurIPS Yue Song, Andy Keller, Nicu Sebe, Max Welling
2023	J	`jnl`	Flow Factorized Representation Learning. CoRR Yue Song, T. Anderson Keller, Nicu Sebe, Max Welling
2023	J	`jnl`	GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers. CoRR Takeru Miyato, Bernhard Jaeger, Max Welling, Andreas Geiger
2023	A*	`conf`	Geometric Clifford Algebra Networks. ICML David Ruhe, Jayesh K. Gupta, Steven De Keninck, Max Welling, Johannes Brandstetter
2023	J	`jnl`	Geometric Clifford Algebra Networks. CoRR David Ruhe, Jayesh K. Gupta, Steven De Keninck, Max Welling, Johannes Brandstetter
2023	J	`jnl`	Image segmentation with traveling waves in an exactly solvable recurrent neural network. CoRR Luisa H. B. Liboni, Roberto C. Budzinski, Alexandra N. Busch, Sindy Löwe, Thomas A. Keller, Max Welling, Lyle E. Muller
2023	A*	`conf`	Latent Traversals in Generative Models as Potential Flows. ICML Yue Song, T. Anderson Keller, Nicu Sebe, Max Welling
2023	J	`jnl`	Latent Traversals in Generative Models as Potential Flows. CoRR Yue Song, Andy Keller, Nicu Sebe, Max Welling
2023	—	`conf`	Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes. ECML/PKDD (1) Tim Bakker, Herke van Hoof, Max Welling
2023	J	`jnl`	Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes. CoRR Tim Bakker, Herke van Hoof, Max Welling
2023	J	`jnl`	Lie Point Symmetry and Physics Informed Networks. CoRR Tara Akhound-Sadegh, Laurence Perreault Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh
2023	A*	`conf`	Lie Point Symmetry and Physics-Informed Networks. NeurIPS Tara Akhound-Sadegh, Laurence Perreault Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh
2023	A*	`conf`	Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally Coupled Oscillatory Recurrent Neural Networks. ICML T. Anderson Keller, Max Welling
2023	A	`conf`	No time to waste: practical statistical contact tracing with few low-bit messages. AISTATS Rob Romijnders, Yuki M. Asano, Christos Louizos, Max Welling
2023	J	`jnl`	Perspectives on the State and Future of Deep Learning - 2023. CoRR Micah Goldblum, Anima Anandkumar, Richard G. Baraniuk, Tom Goldstein, Kyunghyun Cho, Zachary C. Lipton, Melanie Mitchell, Preetum Nakkiran, Max Welling, Andrew Gordon Wilson
2023	J	`jnl`	Pixelated Reconstruction of Foreground Density and Background Surface Brightness in Gravitational Lensing Systems using Recurrent Inference Machines. CoRR Alexandre Adam, Laurence Perreault Levasseur, Yashar Hezaveh, Max Welling
2023	J	`jnl`	Protect Your Score: Contact Tracing With Differential Privacy Guarantees. CoRR Rob Romijnders, Christos Louizos, Yuki M. Asano, Max Welling
2023	A*	`conf`	Rotating Features for Object Discovery. NeurIPS Sindy Löwe, Phillip Lippe, Francesco Locatello, Max Welling
2023	J	`jnl`	Rotating Features for Object Discovery. CoRR Sindy Löwe, Phillip Lippe, Francesco Locatello, Max Welling
2023	J	`jnl`	Scientific discovery in the age of artificial intelligence. Nat. Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun K. Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik
2023	A*	`conf`	Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths. NeurIPS Lars Holdijk, Yuanqi Du, Ferry Hooft, Priyank Jaini, Bernd Ensing, Max Welling
2023	J	`jnl`	The END: An Equivariant Neural Decoder for Quantum Error Correction. CoRR Evgenii Egorov, Roberto Bondesan, Max Welling
2023	J	`jnl`	Traveling Waves Encode the Recent Past and Enhance Sequence Learning. CoRR T. Anderson Keller, Lyle Muller, Terrence J. Sejnowski, Max Welling
2023	A*	`conf`	Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation. NeurIPS Kirill Neklyudov, Jannes Nys, Luca A. Thiede, Juan Carrasquilla, Qiang Liu, Max Welling, Alireza Makhzani
2023	J	`jnl`	Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation. CoRR Kirill Neklyudov, Jannes Nys, Luca A. Thiede, Juan Carrasquilla, Qiang Liu, Max Welling, Alireza Makhzani
2022	J	`jnl`	Adversarial Defense via Image Denoising with Chaotic Encryption. CoRR Shi Hu, Eric T. Nalisnick, Max Welling
2022	A*	`conf`	Alleviating Adversarial Attacks on Variational Autoencoders with MCMC. NeurIPS Anna Kuzina, Max Welling, Jakub M. Tomczak
2022	—	`conf`	Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data. CLeaR Sindy Löwe, David Madras, Richard S. Zemel, Max Welling
2022	A*	`conf`	Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel. NeurIPS ChangYong Oh, Roberto Bondesan, Efstratios Gavves, Max Welling
2022	J	`jnl`	Bayesian Optimization for Macro Placement. CoRR ChangYong Oh, Roberto Bondesan, Dana Kianfar, Rehan Ahmed, Rishubh Khurana, Payal Agarwal, Romain Lepert, Mysore Sriram, Max Welling
2022	J	`jnl`	Clifford Neural Layers for PDE Modeling. CoRR Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K. Gupta
2022	J	`jnl`	Complex-Valued Autoencoders for Object Discovery. CoRR Sindy Löwe, Phillip Lippe, Maja Rudolph, Max Welling
2022	J	`jnl`	Complex-Valued Autoencoders for Object Discovery. Trans. Mach. Learn. Res. Sindy Löwe, Phillip Lippe, Maja Rudolph, Max Welling
2022	B	`conf`	Deep Policy Dynamic Programming for Vehicle Routing Problems. CPAIOR Wouter Kool, Herke van Hoof, Joaquim A. S. Gromicho, Max Welling
2022	J	`jnl`	Defending Variational Autoencoders from Adversarial Attacks with MCMC. CoRR Anna Kuzina, Max Welling, Jakub M. Tomczak
2022	J	`jnl`	Differential Equations and Continuous-Time Deep Learning (Dagstuhl Seminar 22332). Dagstuhl Reports David Duvenaud, Markus Heinonen, Michael Tiemann, Max Welling
2022	J	`jnl`	Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design. CoRR Ilia Igashov, Hannes Stärk, Clément Vignac, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael M. Bronstein, Bruno E. Correia
2022	A*	`conf`	Equivariant Diffusion for Molecule Generation in 3D. ICML Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling
2022	J	`jnl`	Equivariant Diffusion for Molecule Generation in 3D. CoRR Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling
2022	A*	`conf`	Geometric and Physical Quantities improve E(3) Equivariant Message Passing. ICLR Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J. Bekkers, Max Welling
2022	A*	`conf`	Lie Point Symmetry Data Augmentation for Neural PDE Solvers. ICML Johannes Brandstetter, Max Welling, Daniel E. Worrall
2022	J	`jnl`	Lie Point Symmetry Data Augmentation for Neural PDE Solvers. CoRR Johannes Brandstetter, Max Welling, Daniel E. Worrall
2022	A*	`conf`	Message Passing Neural PDE Solvers. ICLR Johannes Brandstetter, Daniel E. Worrall, Max Welling
2022	J	`jnl`	Message Passing Neural PDE Solvers. CoRR Johannes Brandstetter, Daniel E. Worrall, Max Welling
2022	A*	`conf`	Multi-Agent MDP Homomorphic Networks. ICLR Elise van der Pol, Herke van Hoof, Frans A. Oliehoek, Max Welling
2022	—	`conf`	Neural RF SLAM for unsupervised positioning and mapping with channel state information. ICC Shreya Kadambi, Arash Behboodi, Joseph B. Soriaga, Max Welling, Roohollah Amiri, Srinivas Yerramalli, Taesang Yoo
2022	J	`jnl`	Neural RF SLAM for unsupervised positioning and mapping with channel state information. CoRR Shreya Kadambi, Arash Behboodi, Joseph B. Soriaga, Max Welling, Roohollah Amiri, Srinivas Yerramalli, Taesang Yoo
2022	A*	`conf`	On the symmetries of the synchronization problem in Cryo-EM: Multi-Frequency Vector Diffusion Maps on the Projective Plane. NeurIPS Gabriele Cesa, Arash Behboodi, Taco S. Cohen, Max Welling
2022	A	`conf`	Orbital MCMC. AISTATS Kirill Neklyudov, Max Welling
2022	J	`jnl`	Path Integral Stochastic Optimal Control for Sampling Transition Paths. CoRR Lars Holdijk, Yuanqi Du, Ferry Hooft, Priyank Jaini, Bernd Ensing, Max Welling
2022	J	`jnl`	Recent Advancements in Tractable Probabilistic Inference (Dagstuhl Seminar 22161). Dagstuhl Reports Priyank Jaini, Kristian Kersting, Antonio Vergari, Max Welling
2022	—	`conf`	SVNet: Where SO(3) Equivariance Meets Binarization on Point Cloud Representation. 3DV Zhuo Su, Max Welling, Matti Pietikäinen, Li Liu
2022	J	`jnl`	SVNet: Where SO(3) Equivariance Meets Binarization on Point Cloud Representation. CoRR Zhuo Su, Max Welling, Matti Pietikäinen, Li Liu
2022	J	`jnl`	Structure-based Drug Design with Equivariant Diffusion Models. CoRR Arne Schneuing, Yuanqi Du, Charles Harris, Arian R. Jamasb, Ilia Igashov, Weitao Du, Tom L. Blundell, Pietro Lió, Carla Gomes, Max Welling, Michael M. Bronstein, Bruno E. Correia
2021	A*	`conf`	A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups. ICML Marc Finzi, Max Welling, Andrew Gordon Wilson
2021	J	`jnl`	A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups. CoRR Marc Finzi, Max Welling, Andrew Gordon Wilson
2021	J	`jnl`	An Expectation-Maximization Perspective on Federated Learning. CoRR Christos Louizos, Matthias Reisser, Joseph Soriaga, Max Welling
2021	A*	`conf`	Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions. NeurIPS Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling
2021	J	`jnl`	Argmax Flows and Multinomial Diffusion: Towards Non-Autoregressive Language Models. CoRR Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling
2021	J	`jnl`	Batch Bayesian Optimization on Permutations using Acquisition Weighted Kernels. CoRR ChangYong Oh, Roberto Bondesan, Efstratios Gavves, Max Welling
2021	J	`jnl`	Coordinate Independent Convolutional Networks - Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds. CoRR Maurice Weiler, Patrick Forré, Erik Verlinde, Max Welling
2021	J	`jnl`	Deep Policy Dynamic Programming for Vehicle Routing Problems. CoRR Wouter Kool, Herke van Hoof, Joaquim A. S. Gromicho, Max Welling
2021	J	`jnl`	Deterministic Gibbs Sampling via Ordinary Differential Equations. CoRR Kirill Neklyudov, Roberto Bondesan, Max Welling
2021	J	`jnl`	Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks. CoRR Anna Kuzina, Max Welling, Jakub M. Tomczak
2021	A*	`conf`	E(n) Equivariant Graph Neural Networks. ICML Victor Garcia Satorras, Emiel Hoogeboom, Max Welling
2021	J	`jnl`	E(n) Equivariant Graph Neural Networks. CoRR Victor Garcia Satorras, Emiel Hoogeboom, Max Welling
2021	J	`jnl`	E(n) Equivariant Normalizing Flows for Molecule Generation in 3D. CoRR Victor Garcia Satorras, Emiel Hoogeboom, Fabian B. Fuchs, Ingmar Posner, Max Welling
2021	A*	`conf`	E(n) Equivariant Normalizing Flows. NeurIPS Victor Garcia Satorras, Emiel Hoogeboom, Fabian Fuchs, Ingmar Posner, Max Welling
2021	J	`jnl`	Efficient Causal Inference from Combined Observational and Interventional Data through Causal Reductions. CoRR Maximilian Ilse, Patrick Forré, Max Welling, Joris M. Mooij
2021	—	`conf`	Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge. MLMIR@MICCAI Patricia M. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus Van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius Staring, Eric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling, Matthew J. Muckley, Florian Knoll
2021	A*	`conf`	Federated Learning of User Verification Models Without Sharing Embeddings. ICML Hossein Hosseini, Hyunsin Park, Sungrack Yun, Christos Louizos, Joseph Soriaga, Max Welling
2021	J	`jnl`	Federated Learning of User Verification Models Without Sharing Embeddings. CoRR Hossein Hosseini, Hyunsin Park, Sungrack Yun, Christos Louizos, Joseph Soriaga, Max Welling
2021	J	`jnl`	Federated Mixture of Experts. CoRR Matthias Reisser, Christos Louizos, Efstratios Gavves, Max Welling
2021	A*	`conf`	Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. ICLR Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling
2021	J	`jnl`	Geometric and Physical Quantities improve E(3) Equivariant Message Passing. CoRR Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J. Bekkers, Max Welling
2021	A*	`conf`	Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent. NeurIPS Priyank Jaini, Lars Holdijk, Max Welling
2021	J	`jnl`	Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent. CoRR Priyank Jaini, Lars Holdijk, Max Welling
2021	—	`conf`	Learning to Predict Error for MRI Reconstruction. MICCAI (3) Shi Hu, Nicola Pezzotti, Max Welling
2021	J	`jnl`	Mixed Variable Bayesian Optimization with Frequency Modulated Kernels. CoRR ChangYong Oh, Efstratios Gavves, Max Welling
2021	A	`conf`	Mixed variable Bayesian optimization with frequency modulated kernels. UAI ChangYong Oh, Efstratios Gavves, Max Welling
2021	A*	`conf`	Modality-Agnostic Topology Aware Localization. NeurIPS Farhad Ghazvinian Zanjani, Ilia Karmanov, Hanno Ackermann, Daniel Dijkman, Simone Merlin, Max Welling, Fatih Porikli
2021	J	`jnl`	Modeling Category-Selective Cortical Regions with Topographic Variational Autoencoders. CoRR T. Anderson Keller, Qinghe Gao, Max Welling
2021	J	`jnl`	Multi-Agent MDP Homomorphic Networks. CoRR Elise van der Pol, Herke van Hoof, Frans A. Oliehoek, Max Welling
2021	B	`conf`	Neural Augmentation of Kalman Filter with Hypernetwork for Channel Tracking. GLOBECOM Kumar Pratik, Rana Ali Amjad, Arash Behboodi, Joseph B. Soriaga, Max Welling
2021	J	`jnl`	Neural Augmentation of Kalman Filter with Hypernetwork for Channel Tracking. CoRR Kumar Pratik, Rana Ali Amjad, Arash Behboodi, Joseph B. Soriaga, Max Welling
2021	A	`conf`	Neural Enhanced Belief Propagation on Factor Graphs. AISTATS Victor Garcia Satorras, Max Welling
2021	J	`jnl`	Particle Dynamics for Learning EBMs. CoRR Kirill Neklyudov, Priyank Jaini, Max Welling
2021	—	`conf`	Predictive Coding with Topographic Variational Autoencoders. ICCVW T. Anderson Keller, Max Welling
2021	A*	`conf`	Probabilistic Numeric Convolutional Neural Networks. ICLR Marc Anton Finzi, Roberto Bondesan, Max Welling
2021	J	`jnl`	RE-MIMO: Recurrent and Permutation Equivariant Neural MIMO Detection. IEEE Trans. Signal Process. Kumar Pratik, Bhaskar D. Rao, Max Welling
2021	A	`conf`	Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC. AISTATS Priyank Jaini, Didrik Nielsen, Max Welling
2021	J	`jnl`	Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC. CoRR Priyank Jaini, Didrik Nielsen, Max Welling
2021	A*	`conf`	Self Normalizing Flows. ICML T. Anderson Keller, Jorn W. T. Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling
2021	A*	`conf`	The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning. ICML Roberto Bondesan, Max Welling
2021	J	`jnl`	The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning. CoRR Roberto Bondesan, Max Welling
2021	A*	`conf`	Topographic VAEs learn Equivariant Capsules. NeurIPS T. Anderson Keller, Max Welling
2021	J	`jnl`	Topographic VAEs learn Equivariant Capsules. CoRR T. Anderson Keller, Max Welling
2021	—	`conf`	Transformer-Based Deep Survival Analysis. SPACA Shi Hu, Egill A. Fridgeirsson, Guido van Wingen, Max Welling
2020	J	`jnl`	A Data and Compute Efficient Design for Limited-Resources Deep Learning. CoRR Mirgahney Mohamed, Gabriele Cesa, Taco S. Cohen, Max Welling
2020	J	`jnl`	A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. Computer Zeynep Akata, Dan Balliet, Maarten de Rijke, Frank Dignum, Virginia Dignum, Guszti Eiben, Antske Fokkens, Davide Grossi, Koen V. Hindriks, Holger H. Hoos, Hayley Hung, Catholijn M. Jonker, Christof Monz, Mark A. Neerincx, Frans A. Oliehoek, Henry Prakken, Stefan Schlobach, Linda C. van der Gaag, Frank van Harmelen, Herke van Hoof, Birna van Riemsdijk, Aimee van Wynsberghe, Rineke Verbrugge, Bart Verheij, Piek Vossen, Max Welling
2020	J	`jnl`	Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data. CoRR Sindy Löwe, David Madras, Richard S. Zemel, Max Welling
2020	J	`jnl`	Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement. J. Mach. Learn. Res. Wouter Kool, Herke van Hoof, Max Welling
2020	A*	`conf`	Batch-shaping for learning conditional channel gated networks. ICLR Babak Ehteshami Bejnordi, Tijmen Blankevoort, Max Welling
2020	A*	`conf`	Bayesian Bits: Unifying Quantization and Pruning. NeurIPS Mart van Baalen, Christos Louizos, Markus Nagel, Rana Ali Amjad, Ying Wang, Tijmen Blankevoort, Max Welling
2020	J	`jnl`	Bayesian Bits: Unifying Quantization and Pruning. CoRR Mart van Baalen, Christos Louizos, Markus Nagel, Rana Ali Amjad, Ying Wang, Tijmen Blankevoort, Max Welling
2020	A*	`conf`	Contrastive Learning of Structured World Models. ICLR Thomas N. Kipf, Elise van der Pol, Max Welling
2020	—	`conf`	DIVA: Domain Invariant Variational Autoencoders. MIDL Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling
2020	A*	`conf`	Estimating Gradients for Discrete Random Variables by Sampling without Replacement. ICLR Wouter Kool, Herke van Hoof, Max Welling
2020	J	`jnl`	Estimating Gradients for Discrete Random Variables by Sampling without Replacement. CoRR Wouter Kool, Herke van Hoof, Max Welling
2020	A*	`conf`	Experimental design for MRI by greedy policy search. NeurIPS Tim Bakker, Herke van Hoof, Max Welling
2020	J	`jnl`	Experimental design for MRI by greedy policy search. CoRR Tim Bakker, Herke van Hoof, Max Welling
2020	J	`jnl`	Federated Learning of User Authentication Models. CoRR Hossein Hosseini, Sungrack Yun, Hyunsin Park, Christos Louizos, Joseph Soriaga, Max Welling
2020	J	`jnl`	Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. CoRR Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling
2020	A*	`conf`	Gradient $\ell_1$ Regularization for Quantization Robustness. ICLR Milad Alizadeh, Arash Behboodi, Mart van Baalen, Christos Louizos, Tijmen Blankevoort, Max Welling
2020	J	`jnl`	Gradient 𝓁 CoRR Milad Alizadeh, Arash Behboodi, Mart van Baalen, Christos Louizos, Tijmen Blankevoort, Max Welling
2020	J	`jnl`	Graph refinement based airway extraction using mean-field networks and graph neural networks. Medical Image Anal. Raghavendra Selvan, Thomas Kipf, Max Welling, Antonio Garcia-Uceda Juarez, Jesper Holst Pedersen, Jens Petersen, Marleen de Bruijne
2020	A*	`conf`	Guided Variational Autoencoder for Disentanglement Learning. CVPR Zheng Ding, Yifan Xu, Weijian Xu, Gaurav Parmar, Yang Yang, Max Welling, Zhuowen Tu
2020	J	`jnl`	Guided Variational Autoencoder for Disentanglement Learning. CoRR Zheng Ding, Yifan Xu, Weijian Xu, Gaurav Parmar, Yang Yang, Max Welling, Zhuowen Tu
2020	C	`conf`	Integrating Generative Modeling into Deep Learning. ICPRAM Max Welling
2020	A*	`conf`	Involutive MCMC: a Unifying Framework. ICML Kirill Neklyudov, Max Welling, Evgenii Egorov, Dmitry P. Vetrov
2020	J	`jnl`	Involutive MCMC: a Unifying Framework. CoRR Kirill Neklyudov, Max Welling, Evgenii Egorov, Dmitry P. Vetrov
2020	A*	`conf`	MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning. NeurIPS Elise van der Pol, Daniel E. Worrall, Herke van Hoof, Frans A. Oliehoek, Max Welling
2020	J	`jnl`	MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning. CoRR Elise van der Pol, Daniel E. Worrall, Herke van Hoof, Frans A. Oliehoek, Max Welling
2020	A*	`conf`	Natural Graph Networks. NeurIPS Pim de Haan, Taco S. Cohen, Max Welling
2020	J	`jnl`	Natural Graph Networks. CoRR Pim de Haan, Taco Cohen, Max Welling
2020	J	`jnl`	Neural Enhanced Belief Propagation on Factor Graphs. CoRR Victor Garcia Satorras, Max Welling
2020	J	`jnl`	Orbital MCMC. CoRR Kirill Neklyudov, Max Welling
2020	A	`conf`	Plannable Approximations to MDP Homomorphisms: Equivariance under Actions. AAMAS Elise van der Pol, Thomas Kipf, Frans A. Oliehoek, Max Welling
2020	J	`jnl`	Plannable Approximations to MDP Homomorphisms: Equivariance under Actions. CoRR Elise van der Pol, Thomas N. Kipf, Frans A. Oliehoek, Max Welling
2020	J	`jnl`	Probabilistic Numeric Convolutional Neural Networks. CoRR Marc Finzi, Roberto Bondesan, Max Welling
2020	J	`jnl`	Quantum Deformed Neural Networks. CoRR Roberto Bondesan, Max Welling
2020	A	`conf`	Relational Generalized Few-Shot Learning. BMVC Xiahan Shi, Leonard Salewski, Martin Schiegg, Max Welling
2020	A*	`conf`	SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks. NeurIPS Fabian Fuchs, Daniel E. Worrall, Volker Fischer, Max Welling
2020	J	`jnl`	SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks. CoRR Fabian B. Fuchs, Daniel E. Worrall, Volker Fischer, Max Welling
2020	J	`jnl`	Self Normalizing Flows. CoRR T. Anderson Keller, Jorn W. T. Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling
2020	J	`jnl`	Simple and Accurate Uncertainty Quantification from Bias-Variance Decomposition. CoRR Shi Hu, Nicola Pezzotti, Dimitrios Mavroeidis, Max Welling
2020	A*	`conf`	SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. NeurIPS Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling
2020	J	`jnl`	SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. CoRR Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling
2020	A*	`conf`	The Convolution Exponential and Generalized Sylvester Flows. NeurIPS Emiel Hoogeboom, Victor Garcia Satorras, Jakub M. Tomczak, Max Welling
2020	J	`jnl`	The Convolution Exponential and Generalized Sylvester Flows. CoRR Emiel Hoogeboom, Victor Garcia Satorras, Jakub M. Tomczak, Max Welling
2020	A*	`conf`	To Relieve Your Headache of Training an MRF, Take AdVIL. ICLR Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu, Bo Zhang
2020	J	`jnl`	Variational Bayes In Private Settings (VIPS). J. Artif. Intell. Res. Mijung Park, James R. Foulds, Kamalika Chaudhuri, Max Welling
2020	A*	`conf`	Variational Bayes in Private Settings (VIPS) (Extended Abstract). IJCAI James R. Foulds, Mijung Park, Kamalika Chaudhuri, Max Welling
2019	J	`jnl`	Adversarial Variational Inference and Learning in Markov Random Fields. CoRR Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu, Bo Zhang
2019	J	`jnl`	An Introduction to Variational Autoencoders. CoRR Diederik P. Kingma, Max Welling
2019	J	`jnl`	An Introduction to Variational Autoencoders. Found. Trends Mach. Learn. Diederik P. Kingma, Max Welling
2019	—	`conf`	Attention, Learn to Solve Routing Problems! ICLR (Poster) Wouter Kool, Herke van Hoof, Max Welling
2019	J	`jnl`	Batch-Shaped Channel Gated Networks. CoRR Babak Ehteshami Bejnordi, Tijmen Blankevoort, Max Welling
2019	—	`conf`	Buy 4 REINFORCE Samples, Get a Baseline for Free! DeepRLStructPred@ICLR Wouter Kool, Herke van Hoof, Max Welling
2019	J	`jnl`	Combinatorial Bayesian Optimization using Graph Representations. CoRR ChangYong Oh, Jakub M. Tomczak, Efstratios Gavves, Max Welling
2019	A*	`conf`	Combinatorial Bayesian Optimization using the Graph Cartesian Product. NeurIPS ChangYong Oh, Jakub M. Tomczak, Efstratios Gavves, Max Welling
2019	A*	`conf`	Combining Generative and Discriminative Models for Hybrid Inference. NeurIPS Victor Garcia Satorras, Max Welling, Zeynep Akata
2019	J	`jnl`	Combining Generative and Discriminative Models for Hybrid Inference. CoRR Victor Garcia Satorras, Zeynep Akata, Max Welling
2019	J	`jnl`	Contrastive Learning of Structured World Models. CoRR Thomas N. Kipf, Elise van der Pol, Max Welling
2019	J	`jnl`	Covariance in Physics and Convolutional Neural Networks. CoRR Miranda C. N. Cheng, Vassilis Anagiannis, Maurice Weiler, Pim de Haan, Taco S. Cohen, Max Welling
2019	—	`conf`	DIVA: Domain Invariant Variational Autoencoder. DGS@ICLR Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling
2019	J	`jnl`	DIVA: Domain Invariant Variational Autoencoders. CoRR Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling
2019	J	`jnl`	DP-MAC: The Differentially Private Method of Auxiliary Coordinates for Deep Learning. CoRR Frederik Harder, Jonas Köhler, Max Welling, Mijung Park
2019	A*	`conf`	Data-Free Quantization Through Weight Equalization and Bias Correction. ICCV Markus Nagel, Mart van Baalen, Tijmen Blankevoort, Max Welling
2019	J	`jnl`	Data-Free Quantization through Weight Equalization and Bias Correction. CoRR Markus Nagel, Mart van Baalen, Tijmen Blankevoort, Max Welling
2019	A*	`conf`	Deep Scale-spaces: Equivariance Over Scale. NeurIPS Daniel E. Worrall, Max Welling
2019	J	`jnl`	Deep Scale-spaces: Equivariance Over Scale. CoRR Daniel E. Worrall, Max Welling
2019	A	`conf`	Differentiable Probabilistic Models of Scientific Imaging with the Fourier Slice Theorem. UAI Karen Ullrich, Rianne van den Berg, Marcus A. Brubaker, David J. Fleet, Max Welling
2019	J	`jnl`	Differentiable probabilistic models of scientific imaging with the Fourier slice theorem. CoRR Karen Ullrich, Rianne van den Berg, Marcus A. Brubaker, David J. Fleet, Max Welling
2019	A*	`conf`	Emerging Convolutions for Generative Normalizing Flows. ICML Emiel Hoogeboom, Rianne van den Berg, Max Welling
2019	J	`jnl`	Emerging Convolutions for Generative Normalizing Flows. CoRR Emiel Hoogeboom, Rianne van den Berg, Max Welling
2019	A*	`conf`	Gauge Equivariant Convolutional Networks and the Icosahedral CNN. ICML Taco Cohen, Maurice Weiler, Berkay Kicanaoglu, Max Welling
2019	J	`jnl`	Gauge Equivariant Convolutional Networks and the Icosahedral CNN. CoRR Taco S. Cohen, Maurice Weiler, Berkay Kicanaoglu, Max Welling
2019	—	`conf`	Initialized Equilibrium Propagation for Backprop-Free Training. ICLR (Poster) Peter O'Connor, Efstratios Gavves, Max Welling
2019	A*	`conf`	Integer Discrete Flows and Lossless Compression. NeurIPS Emiel Hoogeboom, Jorn W. T. Peters, Rianne van den Berg, Max Welling
2019	J	`jnl`	Integer Discrete Flows and Lossless Compression. CoRR Emiel Hoogeboom, Jorn W. T. Peters, Rianne van den Berg, Max Welling
2019	A*	`conf`	Invert to Learn to Invert. NeurIPS Patrick Putzky, Max Welling
2019	J	`jnl`	Invert to Learn to Invert. CoRR Patrick Putzky, Max Welling
2019	J	`jnl`	Learning Likelihoods with Conditional Normalizing Flows. CoRR Christina Winkler, Daniel E. Worrall, Emiel Hoogeboom, Max Welling
2019	J	`jnl`	Recurrent inference machines for reconstructing heterogeneous MRI data. Medical Image Anal. Kai Lønning, Patrick Putzky, Jan-Jakob Sonke, Liesbeth Reneman, Matthan W. A. Caan, Max Welling
2019	J	`jnl`	Relational Generalized Few-Shot Learning. CoRR Xiahan Shi, Leonard Salewski, Martin Schiegg, Zeynep Akata, Max Welling
2019	—	`conf`	Relaxed Quantization for Discretized Neural Networks. ICLR (Poster) Christos Louizos, Matthias Reisser, Tijmen Blankevoort, Efstratios Gavves, Max Welling
2019	A	`conf`	Sinkhorn AutoEncoders. UAI Giorgio Patrini, Rianne van den Berg, Patrick Forré, Marcello Carioni, Samarth Bhargav, Max Welling, Tim Genewein, Frank Nielsen
2019	—	`conf`	Stochastic Activation Actor Critic Methods. ECML/PKDD (3) Wenling Shang, Douwe van der Wal, Herke van Hoof, Max Welling
2019	A*	`conf`	Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement. ICML Wouter Kool, Herke van Hoof, Max Welling
2019	J	`jnl`	Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement. CoRR Wouter Kool, Herke van Hoof, Max Welling
2019	—	`conf`	Supervised Uncertainty Quantification for Segmentation with Multiple Annotations. MICCAI (2) Shi Hu, Daniel E. Worrall, Stefan Knegt, Bas Veeling, Henkjan J. Huisman, Max Welling
2019	J	`jnl`	Supervised Uncertainty Quantification for Segmentation with Multiple Annotations. CoRR Shi Hu, Daniel E. Worrall, Stefan Knegt, Bastiaan S. Veeling, Henkjan J. Huisman, Max Welling
2019	J	`jnl`	Taxonomy and Evaluation of Structured Compression of Convolutional Neural Networks. CoRR Andrey Kuzmin, Markus Nagel, Saurabh Pitre, Sandeep Pendyam, Tijmen Blankevoort, Max Welling
2019	—	`conf`	The Deep Weight Prior. ICLR (Poster) Andrei Atanov, Arsenii Ashukha, Kirill Struminsky, Dmitry P. Vetrov, Max Welling
2019	A*	`conf`	The Functional Neural Process. NeurIPS Christos Louizos, Xiahan Shi, Klamer Schutte, Max Welling
2019	J	`jnl`	The Functional Neural Process. CoRR Christos Louizos, Xiahan Shi, Klamer Schutte, Max Welling
2019	A	`conf`	Training a Spiking Neural Network with Equilibrium Propagation. AISTATS Peter O'Connor, Efstratios Gavves, Max Welling
2019	J	`jnl`	i-RIM applied to the fastMRI challenge. CoRR Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling
2018	A*	`conf`	3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data. NeurIPS Maurice Weiler, Mario Geiger, Max Welling, Wouter Boomsma, Taco Cohen
2018	J	`jnl`	3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data. CoRR Maurice Weiler, Mario Geiger, Max Welling, Wouter Boomsma, Taco Cohen
2018	J	`jnl`	Attention Solves Your TSP. CoRR Wouter Kool, Max Welling
2018	A*	`conf`	Attention-based Deep Multiple Instance Learning. ICML Maximilian Ilse, Jakub M. Tomczak, Max Welling
2018	J	`jnl`	Attention-based Deep Multiple Instance Learning. CoRR Maximilian Ilse, Jakub M. Tomczak, Max Welling
2018	A*	`conf`	BOCK : Bayesian Optimization with Cylindrical Kernels. ICML ChangYong Oh, Efstratios Gavves, Max Welling
2018	J	`jnl`	BOCK : Bayesian Optimization with Cylindrical Kernels. CoRR ChangYong Oh, Efstratios Gavves, Max Welling
2018	J	`jnl`	Extraction of Airways using Graph Neural Networks. CoRR Raghavendra Selvan, Thomas N. Kipf, Max Welling, Jesper Holst Pedersen, Jens Petersen, Marleen de Bruijne
2018	J	`jnl`	Graph Refinement based Tree Extraction using Mean-Field Networks and Graph Neural Networks. CoRR Raghavendra Selvan, Thomas N. Kipf, Max Welling, Jesper Holst Pedersen, Jens Petersen, Marleen de Bruijne
2018	A*	`conf`	Graphical Generative Adversarial Networks. NeurIPS Chongxuan Li, Max Welling, Jun Zhu, Bo Zhang
2018	J	`jnl`	Graphical Generative Adversarial Networks. CoRR Chongxuan Li, Max Welling, Jun Zhu, Bo Zhang
2018	—	`conf`	HexaConv. ICLR (Poster) Emiel Hoogeboom, Jorn W. T. Peters, Taco S. Cohen, Max Welling
2018	J	`jnl`	HexaConv. CoRR Emiel Hoogeboom, Jorn W. T. Peters, Taco S. Cohen, Max Welling
2018	—	`conf`	Learning Sparse Neural Networks through L_0 Regularization. ICLR (Poster) Christos Louizos, Max Welling, Diederik P. Kingma
2018	—	`conf`	Mean Field Network Based Graph Refinement with Application to Airway Tree Extraction. MICCAI (2) Raghavendra Selvan, Max Welling, Jesper Holst Pedersen, Jens Petersen, Marleen de Bruijne
2018	J	`jnl`	Mean Field Network based Graph Refinement with application to Airway Tree Extraction. CoRR Raghavendra Selvan, Max Welling, Jesper Holst Pedersen, Jens Petersen, Marleen de Bruijne
2018	B	`conf`	Modeling Relational Data with Graph Convolutional Networks. ESWC Michael Sejr Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, Max Welling
2018	A*	`conf`	Neural Relational Inference for Interacting Systems. ICML Thomas N. Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, Richard S. Zemel
2018	J	`jnl`	Neural Relational Inference for Interacting Systems. CoRR Thomas N. Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, Richard S. Zemel
2018	J	`jnl`	Predictive Uncertainty through Quantization. CoRR Bastiaan S. Veeling, Rianne van den Berg, Max Welling
2018	J	`jnl`	Primal-Dual Wasserstein GAN. CoRR Mevlana Gemici, Zeynep Akata, Max Welling
2018	J	`jnl`	Probabilistic Binary Neural Networks. CoRR Jorn W. T. Peters, Max Welling
2018	J	`jnl`	Relaxed Quantization for Discretized Neural Networks. CoRR Christos Louizos, Matthias Reisser, Tijmen Blankevoort, Efstratios Gavves, Max Welling
2018	—	`conf`	Rotation Equivariant CNNs for Digital Pathology. MICCAI (2) Bastiaan S. Veeling, Jasper Linmans, Jim Winkens, Taco Cohen, Max Welling
2018	J	`jnl`	Rotation Equivariant CNNs for Digital Pathology. CoRR Bastiaan S. Veeling, Jasper Linmans, Jim Winkens, Taco Cohen, Max Welling
2018	J	`jnl`	Sample Efficient Semantic Segmentation using Rotation Equivariant Convolutional Networks. CoRR Jasper Linmans, Jim Winkens, Bastiaan S. Veeling, Taco S. Cohen, Max Welling
2018	J	`jnl`	Sinkhorn AutoEncoders. CoRR Giorgio Patrini, Marcello Carioni, Patrick Forré, Samarth Bhargav, Max Welling, Rianne van den Berg, Tim Genewein, Frank Nielsen
2018	—	`conf`	Spherical CNNs. ICLR Taco S. Cohen, Mario Geiger, Jonas Köhler, Max Welling
2018	J	`jnl`	Spherical CNNs. CoRR Taco S. Cohen, Mario Geiger, Jonas Köhler, Max Welling
2018	A	`conf`	Sylvester Normalizing Flows for Variational Inference. UAI Rianne van den Berg, Leonard Hasenclever, Jakub M. Tomczak, Max Welling
2018	J	`jnl`	Sylvester Normalizing Flows for Variational Inference. CoRR Rianne van den Berg, Leonard Hasenclever, Jakub M. Tomczak, Max Welling
2018	—	`conf`	Temporally Efficient Deep Learning with Spikes. ICLR (Poster) Peter O'Connor, Efstratios Gavves, Matthias Reisser, Max Welling
2018	J	`jnl`	The Deep Weight Prior. Modeling a prior distribution for CNNs using generative models. CoRR Andrei Atanov, Arsenii Ashukha, Kirill Struminsky, Dmitry P. Vetrov, Max Welling
2018	A	`conf`	VAE with a VampPrior. AISTATS Jakub M. Tomczak, Max Welling
2017	—	`conf`	Bayesian Compression for Deep Learning. NIPS Christos Louizos, Karen Ullrich, Max Welling
2017	J	`jnl`	Bayesian Compression for Deep Learning. CoRR Christos Louizos, Karen Ullrich, Max Welling
2017	—	`conf`	Causal Effect Inference with Deep Latent-Variable Models. NIPS Christos Louizos, Uri Shalit, Joris M. Mooij, David A. Sontag, Richard S. Zemel, Max Welling
2017	J	`jnl`	Causal Effect Inference with Deep Latent-Variable Models. CoRR Christos Louizos, Uri Shalit, Joris M. Mooij, David A. Sontag, Richard S. Zemel, Max Welling
2017	J	`jnl`	Convolutional Networks for Spherical Signals. CoRR Taco Cohen, Mario Geiger, Jonas Köhler, Max Welling
2017	A	`conf`	DP-EM: Differentially Private Expectation Maximization. AISTATS Mijung Park, James R. Foulds, Kamalika Choudhary, Max Welling
2017	J	`jnl`	Deep Learning with Permutation-invariant Operator for Multi-instance Histopathology Classification. CoRR Jakub M. Tomczak, Maximilian Ilse, Max Welling
2017	J	`jnl`	Graph Convolutional Matrix Completion. CoRR Rianne van den Berg, Thomas N. Kipf, Max Welling
2017	J	`jnl`	Interpretation of microbiota-based diagnostics by explaining individual classifier decisions. BMC Bioinform. A. Eck, Luisa M. Zintgraf, E. F. J. de Groot, Tim G. J. de Meij, Taco S. Cohen, P. H. M. Savelkoul, Max Welling, A. E. Budding
2017	J	`jnl`	Learning Sparse Neural Networks through L CoRR Christos Louizos, Max Welling, Diederik P. Kingma
2017	J	`jnl`	Modeling Relational Data with Graph Convolutional Networks. CoRR Michael Sejr Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, Max Welling
2017	A*	`conf`	Multiplicative Normalizing Flows for Variational Bayesian Neural Networks. ICML Christos Louizos, Max Welling
2017	J	`jnl`	Multiplicative Normalizing Flows for Variational Bayesian Neural Networks. CoRR Christos Louizos, Max Welling
2017	J	`jnl`	Recurrent Inference Machines for Solving Inverse Problems. CoRR Patrick Putzky, Max Welling
2017	—	`conf`	Semi-Supervised Classification with Graph Convolutional Networks. ICLR (Poster) Thomas N. Kipf, Max Welling
2017	—	`conf`	Sigma Delta Quantized Networks. ICLR (Poster) Peter O'Connor, Max Welling
2017	—	`conf`	Soft Weight-Sharing for Neural Network Compression. ICLR (Poster) Karen Ullrich, Edward Meeds, Max Welling
2017	J	`jnl`	Soft Weight-Sharing for Neural Network Compression. CoRR Karen Ullrich, Edward Meeds, Max Welling
2017	—	`conf`	Steerable CNNs. ICLR (Poster) Taco S. Cohen, Max Welling
2017	J	`jnl`	Temporally Efficient Deep Learning with Spikes. CoRR Peter O'Connor, Efstratios Gavves, Max Welling
2017	J	`jnl`	VAE with a VampPrior. CoRR Jakub M. Tomczak, Max Welling
2017	—	`conf`	Visualizing Deep Neural Network Decisions: Prediction Difference Analysis. ICLR (Poster) Luisa M. Zintgraf, Taco S. Cohen, Tameem Adel, Max Welling
2017	J	`jnl`	Visualizing Deep Neural Network Decisions: Prediction Difference Analysis. CoRR Luisa M. Zintgraf, Taco S. Cohen, Tameem Adel, Max Welling
2016	J	`jnl`	A New Method to Visualize Deep Neural Networks. CoRR Luisa M. Zintgraf, Taco S. Cohen, Max Welling
2016	J	`jnl`	A note on privacy preserving iteratively reweighted least squares. CoRR Mijung Park, Max Welling
2016	—	`ed.`	Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part I ECCV (1) Bastian Leibe, Jiri Matas, Nicu Sebe, Max Welling
2016	—	`ed.`	Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part II ECCV (2) Bastian Leibe, Jiri Matas, Nicu Sebe, Max Welling
2016	—	`ed.`	Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part III ECCV (3) Bastian Leibe, Jiri Matas, Nicu Sebe, Max Welling
2016	—	`ed.`	Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part IV ECCV (4) Bastian Leibe, Jiri Matas, Nicu Sebe, Max Welling
2016	—	`ed.`	Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part V ECCV (5) Bastian Leibe, Jiri Matas, Nicu Sebe, Max Welling
2016	—	`ed.`	Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VI ECCV (6) Bastian Leibe, Jiri Matas, Nicu Sebe, Max Welling
2016	—	`ed.`	Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VII ECCV (7) Bastian Leibe, Jiri Matas, Nicu Sebe, Max Welling
2016	—	`ed.`	Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VIII ECCV (8) Bastian Leibe, Jiri Matas, Nicu Sebe, Max Welling
2016	J	`jnl`	Deep Spiking Networks. CoRR Peter O'Connor, Max Welling
2016	A*	`conf`	Group Equivariant Convolutional Networks. ICML Taco Cohen, Max Welling
2016	J	`jnl`	Group Equivariant Convolutional Networks. CoRR Taco S. Cohen, Max Welling
2016	J	`jnl`	Herded Gibbs Sampling. J. Mach. Learn. Res. Yutian Chen, Luke Bornn, Nando de Freitas, Mareija Eskelin, Jing Fang, Max Welling
2016	J	`jnl`	Herding as a Learning System with Edge-of-Chaos Dynamics. CoRR Yutian Chen, Max Welling
2016	J	`jnl`	Improving Variational Auto-Encoders using Householder Flow. CoRR Jakub M. Tomczak, Max Welling
2016	—	`conf`	Improving Variational Autoencoders with Inverse Autoregressive Flow. NIPS Diederik P. Kingma, Tim Salimans, Rafal Józefowicz, Xi Chen, Ilya Sutskever, Max Welling
2016	J	`jnl`	Improving Variational Inference with Inverse Autoregressive Flow. CoRR Diederik P. Kingma, Tim Salimans, Max Welling
2016	J	`jnl`	Marrying Graphical Models with Deep Learning. ERCIM News Max Welling
2016	A	`conf`	On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis. UAI James R. Foulds, Joseph Geumlek, Max Welling, Kamalika Chaudhuri
2016	J	`jnl`	On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis. CoRR James R. Foulds, Joseph Geumlek, Max Welling, Kamalika Chaudhuri
2016	J	`jnl`	Practical Privacy For Expectation Maximization. CoRR Mijung Park, Jimmy Foulds, Kamalika Chaudhuri, Max Welling
2016	J	`jnl`	Private Topic Modeling. CoRR Mijung Park, James R. Foulds, Kamalika Chaudhuri, Max Welling
2016	A	`conf`	Scalable MCMC for Mixed Membership Stochastic Blockmodels. AISTATS Wenzhe Li, Sungjin Ahn, Max Welling
2016	—	`conf`	Scalable Overlapping Community Detection. IPDPS Workshops Ismail El-Helw, Rutger F. H. Hofman, Wenzhe Li, Sungjin Ahn, Max Welling, Henri E. Bal
2016	J	`jnl`	Semi-Supervised Classification with Graph Convolutional Networks. CoRR Thomas N. Kipf, Max Welling
2016	J	`jnl`	Sequential Tests for Large-Scale Learning. Neural Comput. Anoop Korattikara, Yutian Chen, Max Welling
2016	J	`jnl`	Sigma Delta Quantized Networks. CoRR Peter O'Connor, Max Welling
2016	J	`jnl`	Steerable CNNs. CoRR Taco S. Cohen, Max Welling
2016	A*	`conf`	Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors. ICML Christos Louizos, Max Welling
2016	J	`jnl`	Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors. CoRR Christos Louizos, Max Welling
2016	A*	`conf`	The Variational Fair Autoencoder. ICLR Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, Richard S. Zemel
2016	J	`jnl`	Variational Bayes In Private Settings (VIPS). CoRR Mijung Park, James R. Foulds, Kamalika Chaudhuri, Max Welling
2016	J	`jnl`	Variational Graph Auto-Encoders. CoRR Thomas N. Kipf, Max Welling
2015	J	`jnl`	Bayesian Dark Knowledge. CoRR Anoop Korattikara Balan, Vivek Rathod, Kevin Murphy, Max Welling
2015	—	`conf`	Bayesian dark knowledge. NIPS Anoop Korattikara Balan, Vivek Rathod, Kevin P. Murphy, Max Welling
2015	A	`conf`	Hamiltonian ABC. UAI Edward Meeds, Robert Leenders, Max Welling
2015	J	`jnl`	Hamiltonian ABC. CoRR Edward Meeds, Robert Leenders, Max Welling
2015	A*	`conf`	Harmonic Exponential Families on Manifolds. ICML Taco Cohen, Max Welling
2015	A*	`conf`	Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC. KDD Sungjin Ahn, Anoop Korattikara, Nathan Liu, Suju Rajan, Max Welling
2015	J	`jnl`	Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC. CoRR Sungjin Ahn, Anoop Korattikara Balan, Nathan Liu, Suju Rajan, Max Welling
2015	J	`jnl`	MLitB: machine learning in the browser. PeerJ Comput. Sci. Edward Meeds, Remco Hendriks, Said al Faraby, Magiel Bruntink, Max Welling
2015	A*	`conf`	Markov Chain Monte Carlo and Variational Inference: Bridging the Gap. ICML Tim Salimans, Diederik P. Kingma, Max Welling
2015	—	`conf`	Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference. NIPS Edward Meeds, Max Welling
2015	J	`jnl`	Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference. CoRR Edward Meeds, Max Welling
2015	J	`jnl`	POPE: post optimization posterior evaluation of likelihood free models. BMC Bioinform. Edward Meeds, Michael Chiang, Mary Lee, Olivier Cinquin, John S. Lowengrub, Max Welling
2015	J	`jnl`	Scalable MCMC for Mixed Membership Stochastic Blockmodels. CoRR Wenzhe Li, Sungjin Ahn, Max Welling
2015	—	`conf`	Transformation Properties of Learned Visual Representations. ICLR (Poster) Taco S. Cohen, Max Welling
2015	—	`conf`	Variational Dropout and the Local Reparameterization Trick. NIPS Diederik P. Kingma, Tim Salimans, Max Welling
2015	J	`jnl`	Variational Dropout and the Local Reparameterization Trick. CoRR Diederik P. Kingma, Tim Salimans, Max Welling
2014	—	`ed.`	Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada NIPS Zoubin Ghahramani, Max Welling, Corinna Cortes, Neil D. Lawrence, Kilian Q. Weinberger
2014	A	`conf`	Approximate Slice Sampling for Bayesian Posterior Inference. AISTATS Christopher DuBois, Anoop Korattikara Balan, Max Welling, Padhraic Smyth
2014	A*	`conf`	Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget. ICML Anoop Korattikara Balan, Yutian Chen, Max Welling
2014	—	`conf`	Auto-Encoding Variational Bayes. ICLR Diederik P. Kingma, Max Welling
2014	J	`jnl`	Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior. CoRR Yutian Chen, Max Welling
2014	A*	`conf`	Distributed Stochastic Gradient MCMC. ICML Sungjin Ahn, Babak Shahbaba, Max Welling
2014	A*	`conf`	Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets. ICML Diederik P. Kingma, Max Welling
2014	J	`jnl`	Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets. CoRR Diederik P. Kingma, Max Welling
2014	J	`jnl`	Exploiting the Statistics of Learning and Inference. CoRR Max Welling
2014	A	`conf`	GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation. UAI Edward Meeds, Max Welling
2014	J	`jnl`	GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation. CoRR Edward Meeds, Max Welling
2014	A*	`conf`	Learning the Irreducible Representations of Commutative Lie Groups. ICML Taco Cohen, Max Welling
2014	J	`jnl`	Learning the Irreducible Representations of Commutative Lie Groups. CoRR Taco Cohen, Max Welling
2014	J	`jnl`	MLitB: Machine Learning in the Browser. CoRR Edward Meeds, Remco Hendriks, Said al Faraby, Magiel Bruntink, Max Welling
2014	J	`jnl`	Semi-Supervised Learning with Deep Generative Models. CoRR Diederik P. Kingma, Danilo Jimenez Rezende, Shakir Mohamed, Max Welling
2014	—	`conf`	Semi-supervised Learning with Deep Generative Models. NIPS Diederik P. Kingma, Shakir Mohamed, Danilo Jimenez Rezende, Max Welling
2013	A*	`conf`	A Lazy Man's Approach to Benchmarking: Semisupervised Classifier Evaluation and Recalibration. CVPR Peter Welinder, Max Welling, Pietro Perona
2013	J	`jnl`	Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget CoRR Anoop Korattikara Balan, Yutian Chen, Max Welling
2013	J	`jnl`	Belief Optimization for Binary Networks: A Stable Alternative to Loopy Belief Propagation CoRR Max Welling, Yee Whye Teh
2013	A	`conf`	Distributed and Adaptive Darting Monte Carlo through Regenerations. AISTATS Sungjin Ahn, Yutian Chen, Max Welling
2013	A	`conf`	Evidence Estimation for Bayesian Partially Observed MRFs. AISTATS Yutian Chen, Max Welling
2013	A*	`conf`	Herded Gibbs Sampling ICLR Luke Bornn, Yutian Chen, Nando de Freitas, Mareija Eskelin, Jing Fang, Max Welling
2013	J	`jnl`	Stochastic Collapsed Variational Bayesian Inference for Latent Dirichlet Allocation CoRR James R. Foulds, Levi Boyles, Christopher DuBois, Padhraic Smyth, Max Welling
2013	A*	`conf`	Stochastic collapsed variational Bayesian inference for latent Dirichlet allocation. KDD James R. Foulds, Levi Boyles, Christopher DuBois, Padhraic Smyth, Max Welling
2012	J	`jnl`	A Cluster-Cumulant Expansion at the Fixed Points of Belief Propagation CoRR Max Welling, Andrew E. Gelfand, Alexander Ihler
2012	A	`conf`	A Cluster-Cumulant Expansion at the Fixed Points of Belief Propagation. UAI Max Welling, Andrew Gelfand, Alexander Ihler
2012	A*	`conf`	Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring. ICML Sungjin Ahn, Anoop Korattikara Balan, Max Welling
2012	J	`jnl`	Bayesian Random Fields: The Bethe-Laplace Approximation. CoRR Max Welling, Sridevi Parise
2012	J	`jnl`	Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior CoRR Yutian Chen, Max Welling
2012	A	`conf`	Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior. UAI Yutian Chen, Max Welling
2012	J	`jnl`	Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell. Ramin Zabih, Sing Bing Kang, Neil D. Lawrence, Jiri Matas, Max Welling
2012	J	`jnl`	Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell. Ramin Zabih, Sing Bing Kang, Neil D. Lawrence, Jiri Matas, Max Welling
2012	J	`jnl`	Efficient Parametric Projection Pursuit Density Estimation CoRR Max Welling, Richard S. Zemel, Geoffrey E. Hinton
2012	Misc	`conf`	Exchangeable inconsistent priors for Bayesian posterior inference. ITA Max Welling, Ian Porteous, Kenichi Kurihara
2012	J	`jnl`	Generalized Belief Propagation on Tree Robust Structured Region Graphs CoRR Andrew Gelfand, Max Welling
2012	A	`conf`	Generalized Belief Propagation on Tree Robust Structured Region Graphs. UAI Andrew Gelfand, Max Welling
2012	J	`jnl`	Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation. CoRR Ian Porteous, Alexander T. Ihler, Padhraic Smyth, Max Welling
2012	J	`jnl`	Herding Dynamic Weights for Partially Observed Random Field Models CoRR Max Welling
2012	J	`jnl`	Hybrid Variational/Gibbs Collapsed Inference in Topic Models CoRR Max Welling, Yee Whye Teh, Hilbert J. Kappen
2012	J	`jnl`	On Smoothing and Inference for Topic Models CoRR Arthur U. Asuncion, Max Welling, Padhraic Smyth, Yee Whye Teh
2012	J	`jnl`	On the Choice of Regions for Generalized Belief Propagation CoRR Max Welling
2012	J	`jnl`	Predicting simulation parameters of biological systems using a Gaussian process model. Stat. Anal. Data Min. Xiangxin Zhu, Max Welling, Fang Jin, John S. Lowengrub
2012	A	`conf`	Scalable Inference on Kingman's Coalescent using Pair Similarity . AISTATS Dilan Görür, Levi Boyles, Max Welling
2012	J	`jnl`	Semisupervised Classifier Evaluation and Recalibration CoRR Peter Welinder, Max Welling, Pietro Perona
2012	J	`jnl`	State of the Journal. IEEE Trans. Pattern Anal. Mach. Intell. Sing Bing Kang, Jiri Matas, Max Welling, Ramin Zabih
2012	J	`jnl`	Structured Region Graphs: Morphing EP into GBP CoRR Max Welling, Thomas P. Minka, Yee Whye Teh
2012	J	`jnl`	Super-Samples from Kernel Herding CoRR Yutian Chen, Max Welling, Alexander J. Smola
2012	—	`conf`	The Time-Marginalized Coalescent Prior for Hierarchical Clustering. NIPS Levi Boyles, Max Welling
2011	A*	`conf`	Bayesian Learning via Stochastic Gradient Langevin Dynamics. ICML Max Welling, Yee Whye Teh
2011	J	`jnl`	Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell. Ramin Zabih, Sing Bing Kang, Jiri Matas, Max Welling
2011	J	`jnl`	Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell. Ramin Zabih, Sing Bing Kang, Jiri Matas, Max Welling
2011	J	`jnl`	Generalized darting Monte Carlo. Pattern Recognit. Cristian Sminchisescu, Max Welling
2011	A	`conf`	Hidden-Unit Conditional Random Fields. AISTATS Laurens van der Maaten, Max Welling, Lawrence K. Saul
2011	A*	`conf`	Integrating local classifiers through nonlinear dynamics on label graphs with an application to image segmentation. ICCV Yutian Chen, Andrew Gelfand, Charless C. Fowlkes, Max Welling
2011	A	`conf`	Statistical Optimization of Non-Negative Matrix Factorization. AISTATS Anoop Korattikara Balan, Levi Boyles, Max Welling, Jingu Kim, Haesun Park
2011	—	`conf`	Statistical Tests for Optimization Efficiency. NIPS Levi Boyles, Anoop Korattikara Balan, Deva Ramanan, Max Welling
2011	J	`jnl`	Unsupervised Organization of Image Collections: Taxonomies and Beyond. IEEE Trans. Pattern Anal. Mach. Intell. Evgeniy Bart, Max Welling, Pietro Perona
2010	A*	`conf`	Bayesian Matrix Factorization with Side Information and Dirichlet Process Mixtures. AAAI Ian Porteous, Arthur U. Asuncion, Max Welling
2010	A*	`conf`	Dynamical Products of Experts for Modeling Financial Time Series. ICML Yutian Chen, Max Welling
2010	J	`jnl`	Localization Algorithms for Wireless Sensor Retrieval. Comput. J. Yuan Zhang, Lichun Bao, Shih-Hsien Yang, Max Welling, Di Wu
2010	—	`conf`	On Herding and the Perceptron Cycling Theorem. NIPS Andrew Gelfand, Yutian Chen, Laurens van der Maaten, Max Welling
2010	A	`conf`	Parametric Herding. AISTATS Yutian Chen, Max Welling
2010	A	`conf`	Super-Samples from Kernel Herding. UAI Yutian Chen, Max Welling, Alexander J. Smola
2009	—	`conf`	Base Station Localization in Search of Empty Spectrum Spaces in Cognitive Radio Networks. MSN Yuan Zhang, Lichun Bao, Max Welling, Shih-Hsien Yang
2009	J	`jnl`	Bayesian Neural Comput. Kenichi Kurihara, Max Welling
2009	A*	`conf`	Bayesian Extreme Components Analysis. IJCAI Yutian Chen, Max Welling
2009	J	`jnl`	Distributed Algorithms for Topic Models. J. Mach. Learn. Res. David Newman, Arthur U. Asuncion, Padhraic Smyth, Max Welling
2009	A	`conf`	Herding Dynamic Weights for Partially Observed Random Field Models. UAI Max Welling
2009	A*	`conf`	Herding dynamical weights to learn. ICML Max Welling
2009	A	`conf`	On Smoothing and Inference for Topic Models. UAI Arthur U. Asuncion, Max Welling, Padhraic Smyth, Yee Whye Teh
2009	A	`conf`	Preface. AISTATS David A. Van Dyk, Max Welling
2009	A	`ed.`	Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, AISTATS 2009, Clearwater Beach, Florida, USA, April 16-18, 2009 AISTATS David A. Van Dyk, Max Welling
2008	—	`conf`	Asynchronous Distributed Learning of Topic Models. NIPS Arthur U. Asuncion, Padhraic Smyth, Max Welling
2008	A	`conf`	Deterministic Latent Variable Models and Their Pitfalls. SDM Max Welling, Chaitanya Chemudugunta, Nathan Sutter
2008	A*	`conf`	Fast collapsed gibbs sampling for latent dirichlet allocation. KDD Ian Porteous, David Newman, Alexander Ihler, Arthur U. Asuncion, Padhraic Smyth, Max Welling
2008	J	`jnl`	Hybrid Generative-Discriminative Visual Categorization. Int. J. Comput. Vis. Alex Holub, Max Welling, Pietro Perona
2008	A	`conf`	Hybrid Variational/Gibbs Collapsed Inference in Topic Models. UAI Max Welling, Yee Whye Teh, Bert Kappen
2008	A*	`conf`	Incremental learning of nonparametric Bayesian mixture models. CVPR Ryan Gomes, Max Welling, Pietro Perona
2008	A*	`conf`	Memory bounded inference in topic models. ICML Ryan Gomes, Max Welling, Pietro Perona
2008	A*	`conf`	Multi-HDP: A Non Parametric Bayesian Model for Tensor Factorization. AAAI Ian Porteous, Evgeniy Bart, Max Welling
2008	A*	`conf`	Unsupervised learning of visual taxonomies. CVPR Evgeniy Bart, Ian Porteous, Pietro Perona, Max Welling
2007	—	`conf`	A Distributed Message Passing Algorithm for Sensor Localization. ICANN (1) Max Welling, Joseph J. Lim
2007	A*	`conf`	Collapsed Variational Dirichlet Process Mixture Models. IJCAI Kenichi Kurihara, Max Welling, Yee Whye Teh
2007	—	`conf`	Collapsed Variational Inference for HDP. NIPS Yee Whye Teh, Kenichi Kurihara, Max Welling
2007	—	`conf`	Distributed Inference for Latent Dirichlet Allocation. NIPS David Newman, Arthur U. Asuncion, Padhraic Smyth, Max Welling
2007	A	`conf`	Generalized Darting Monte Carlo. AISTATS Cristian Sminchisescu, Max Welling
2007	—	`conf`	Infinite State Bayes-Nets for Structured Domains. NIPS Max Welling, Ian Porteous, Evgeniy Bart
2007	J	`jnl`	Product of experts. Scholarpedia Max Welling
2006	—	`conf`	A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation. NIPS Yee Whye Teh, David Newman, Max Welling
2006	—	`conf`	Accelerated Variational Dirichlet Process Mixtures. NIPS Kenichi Kurihara, Max Welling, Nikos Vlassis
2006	A	`conf`	Bayesian K-Means as a "Maximization-Expectation" Algorithm. SDM Max Welling, Kenichi Kurihara
2006	—	`conf`	Bayesian Model Scoring in Markov Random Fields. NIPS Sridevi Parise, Max Welling
2006	A	`conf`	Bayesian Random Fields: The Bethe-Laplace Approximation. UAI Max Welling, Sridevi Parise
2006	A	`conf`	Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation. UAI Ian Porteous, Alexander T. Ihler, Padhraic Smyth, Max Welling
2006	A*	`conf`	The rate adapting poisson model for information retrieval and object recognition. ICML Peter V. Gehler, Alex Holub, Max Welling
2006	J	`jnl`	Topographic Product Models Applied to Natural Scene Statistics. Neural Comput. Simon Osindero, Max Welling, Geoffrey E. Hinton
2006	J	`jnl`	Unsupervised Discovery of Nonlinear Structure Using Contrastive Backpropagation. Cogn. Sci. Geoffrey E. Hinton, Simon Osindero, Max Welling, Yee Whye Teh
2005	A	`conf`	An Expectation Maximization Algorithm for Inferring Offset-Normal Shape Distributions. AISTATS Max Welling
2005	A*	`conf`	Combining Generative Models and Fisher Kernels for Object Recognition. ICCV Alex Holub, Max Welling, Pietro Perona
2005	A	`conf`	Learning in Markov Random Fields with Contrastive Free Energies. AISTATS Max Welling, Charles Sutton
2005	—	`conf`	Products of Edge-perts. NIPS Peter V. Gehler, Max Welling
2005	A	`conf`	Robust Higher Order Statistics. AISTATS Max Welling
2005	A	`conf`	Structured Region Graphs: Morphing EP into GBP. UAI Max Welling, Thomas P. Minka, Yee Whye Teh
2004	A*	`conf`	Approximate inference by Markov chains on union spaces. ICML Max Welling, Michal Rosen-Zvi, Yee Whye Teh
2004	—	`conf`	Exponential Family Harmoniums with an Application to Information Retrieval. NIPS Max Welling, Michal Rosen-Zvi, Geoffrey E. Hinton
2004	J	`jnl`	Linear Response Algorithms for Approximate Inference in Graphical Models. Neural Comput. Max Welling, Yee Whye Teh
2004	A	`conf`	On the Choice of Regions for Generalized Belief Propagation. UAI Max Welling
2004	J	`jnl`	Probabilistic sequential independent components analysis. IEEE Trans. Neural Networks Max Welling, Richard S. Zemel, Geoffrey E. Hinton
2003	J	`jnl`	Approximate inference in Boltzmann machines. Artif. Intell. Max Welling, Yee Whye Teh
2003	A	`conf`	Efficient Parametric Projection Pursuit Density Estimation. UAI Max Welling, Richard S. Zemel, Geoffrey E. Hinton
2003	J	`jnl`	Energy-Based Models for Sparse Overcomplete Representations. J. Mach. Learn. Res. Yee Whye Teh, Max Welling, Simon Osindero, Geoffrey E. Hinton
2003	—	`conf`	Extreme Components Analysis. NIPS Max Welling, Felix V. Agakov, Christopher K. I. Williams
2003	—	`conf`	Linear Response for Approximate Inference. NIPS Max Welling, Yee Whye Teh
2003	A	`conf`	On Improving the Efficiency of the Iterative Proportional Fitting Procedure. AISTATS Yee Whye Teh, Max Welling
2003	—	`conf`	Wormholes Improve Contrastive Divergence. NIPS Geoffrey E. Hinton, Max Welling, Andriy Mnih
2002	C	`conf`	A New Learning Algorithm for Mean Field Boltzmann Machines. ICANN Max Welling, Geoffrey E. Hinton
2002	—	`conf`	Learning Sparse Topographic Representations with Products of Student-t Distributions. NIPS Max Welling, Geoffrey E. Hinton, Simon Osindero
2002	—	`conf`	Self Supervised Boosting. NIPS Max Welling, Richard S. Zemel, Geoffrey E. Hinton
2001	J	`jnl`	A Constrained EM Algorithm for Independent Component Analysis. Neural Comput. Max Welling, Markus Weber
2001	A	`conf`	Belief Optimization for Binary Networks: A Stable Alternative to Loopy Belief Propagation. UAI Max Welling, Yee Whye Teh
2001	J	`jnl`	Positive tensor factorization. Pattern Recognit. Lett. Max Welling, Markus Weber
2001	—	`conf`	The Unified Propagation and Scaling Algorithm. NIPS Yee Whye Teh, Max Welling
2000	A*	`conf`	Towards Automatic Discovery of Object Categories. CVPR Markus Weber, Max Welling, Pietro Perona
2000	—	`conf`	Unsupervised Learning of Models for Recognition. ECCV (1) Markus Weber, Max Welling, Pietro Perona
2000	B	`conf`	Viewpoint-Invariant Learning and Detection of Human Heads. FG Markus Weber, Wolfgang Einhäuser, Max Welling, Pietro Perona