Francesco Locatello

184 papers A* 58A 6Journal 106Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Theory of How Pretraining Shapes Inductive Bias in Fine-Tuning. CoRR Nicolas Anguita, Francesco Locatello, Andrew M. Saxe, Marco Mondelli, Flavia Mancini, Samuel Lippl, Clémentine C. J. Dominé
2026	J	`jnl`	Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning. CoRR Shimeng Huang, Matthew Robinson, Francesco Locatello
2026	—	`ed.`	Pattern Recognition - 47th DAGM German Conference, DAGM GCPR 2025, Freiburg, Germany, September 23-26, 2025, Proceedings DAGM GCPR Margret Keuper, Francesco Locatello
2026	J	`jnl`	Statistical and structural identifiability in representation learning. CoRR Walter Nelson, Marco Fumero, Theofanis Karaletsos, Francesco Locatello
2025	J	`jnl`	Boomerang Distillation Enables Zero-Shot Model Size Interpolation. CoRR Sara Kangaslahti, Nihal V. Nayak, Jonathan Geuter, Marco Fumero, Francesco Locatello, David Alvarez-Melis
2025	J	`jnl`	Causal Lifting of Neural Representations: Zero-Shot Generalization for Causal Inferences. CoRR Riccardo Cadei, Ilker Demirel, Piersilvio De Bartolomeis, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, Francesco Locatello
2025	J	`jnl`	Connecting Neural Models Latent Geometries with Relative Geodesic Representations. CoRR Hanlin Yu, Berfin Inal, Georgios Arvanitidis, Søren Hauberg, Francesco Locatello, Marco Fumero
2025	J	`jnl`	Demystifying amortized causal discovery with transformers. Trans. Mach. Learn. Res. Francesco Montagna, Max Cairney-Leeming, Dhanya Sridhar, Francesco Locatello
2025	J	`jnl`	Exploratory Causal Inference in SAEnce. CoRR Tommaso Mencattini, Riccardo Cadei, Francesco Locatello
2025	J	`jnl`	Head Pursuit: Probing Attention Specialization in Multimodal Transformers. CoRR Lorenzo Basile, Valentino Maiorca, Diego Doimo, Francesco Locatello, Alberto Cazzaniga
2025	J	`jnl`	High-dimensional Analysis of Synthetic Data Selection. CoRR Parham Rezaei, Filip Kovacevic, Francesco Locatello, Marco Mondelli
2025	A*	`conf`	How to Probe: Simple Yet Effective Techniques for Improving Post-hoc Explanations. ICLR Siddhartha Gairola, Moritz Böhle, Francesco Locatello, Bernt Schiele
2025	J	`jnl`	How to Probe: Simple Yet Effective Techniques for Improving Post-hoc Explanations. CoRR Siddhartha Gairola, Moritz Böhle, Francesco Locatello, Bernt Schiele
2025	J	`jnl`	Learning Explicit Single-Cell Dynamics Using ODE Representations. CoRR Jan-Philipp von Bassewitz, Adeel Pervez, Marco Fumero, Matthew Robinson, Theofanis Karaletsos, Francesco Locatello
2025	A*	`conf`	Mechanistic PDE Networks for Discovery of Governing Equations. ICML Adeel Pervez, Efstratios Gavves, Francesco Locatello
2025	J	`jnl`	Mechanistic PDE Networks for Discovery of Governing Equations. CoRR Adeel Pervez, Efstratios Gavves, Francesco Locatello
2025	J	`jnl`	MorphGen: Controllable and Morphologically Plausible Generative Cell-Imaging. CoRR Berker Demirel, Marco Fumero, Theofanis Karaletsos, Francesco Locatello
2025	J	`jnl`	Navigating the Latent Space Dynamics of Neural Models. CoRR Marco Fumero, Luca Moschella, Emanuele Rodolà, Francesco Locatello
2025	A*	`conf`	Near, far: Patch-ordering enhances vision foundation models' scene understanding. ICLR Valentinos Pariza, Mohammadreza Salehi, Gertjan J. Burghouts, Francesco Locatello, Yuki M. Asano
2025	J	`jnl`	ResiDual Transformer Alignment with Spectral Decomposition. Trans. Mach. Learn. Res. Lorenzo Basile, Valentino Maiorca, Luca Bortolussi, Emanuele Rodolà, Francesco Locatello
2025	A*	`conf`	Scalable Mechanistic Neural Networks. ICLR Jiale Chen, Dingling Yao, Adeel Pervez, Dan Alistarh, Francesco Locatello
2025	—	`conf`	Score matching through the roof: linear, nonlinear, and latent variables causal discovery. CLeaR Francesco Montagna, Philipp Michael Faller, Patrick Blöbaum, Elke Kirschbaum, Francesco Locatello
2025	J	`jnl`	The Third Pillar of Causal Analysis? A Measurement Perspective on Causal Representations. CoRR Dingling Yao, Shimeng Huang, Riccardo Cadei, Kun Zhang, Francesco Locatello
2025	A*	`conf`	Unifying Causal Representation Learning with the Invariance Principle. ICLR Dingling Yao, Dario Rancati, Riccardo Cadei, Marco Fumero, Francesco Locatello
2024	A*	`conf`	A Sparsity Principle for Partially Observable Causal Representation Learning. ICML Danru Xu, Dingling Yao, Sébastien Lachapelle, Perouz Taslakian, Julius von Kügelgen, Francesco Locatello, Sara Magliacane
2024	J	`jnl`	A Sparsity Principle for Partially Observable Causal Representation Learning. CoRR Danru Xu, Dingling Yao, Sébastien Lachapelle, Perouz Taslakian, Julius von Kügelgen, Francesco Locatello, Sara Magliacane
2024	A*	`conf`	Adaptive Slot Attention: Object Discovery with Dynamic Slot Number. CVPR Ke Fan, Zechen Bai, Tianjun Xiao, Tong He, Max Horn, Yanwei Fu, Francesco Locatello, Zheng Zhang
2024	J	`jnl`	Adaptive Slot Attention: Object Discovery with Dynamic Slot Number. CoRR Ke Fan, Zechen Bai, Tianjun Xiao, Tong He, Max Horn, Yanwei Fu, Francesco Locatello, Zheng Zhang
2024	J	`jnl`	Adjusting Pretrained Backbones for Performativity. CoRR Berker Demirel, Lingjing Kong, Kun Zhang, Theofanis Karaletsos, Celestine Mendler-Dünner, Francesco Locatello
2024	J	`jnl`	Binding Dynamics in Rotating Features. CoRR Sindy Löwe, Francesco Locatello, Max Welling
2024	—	`ed.`	Causal Learning and Reasoning, 1-3 April 2024, Los Angeles, California, USA. CLeaR Francesco Locatello, Vanessa Didelez
2024	J	`jnl`	Demystifying amortized causal discovery with transformers. CoRR Francesco Montagna, Max Cairney-Leeming, Dhanya Sridhar, Francesco Locatello
2024	A*	`conf`	Grounded Object-Centric Learning. ICLR Avinash Kori, Francesco Locatello, Fabio De Sousa Ribeiro, Francesca Toni, Ben Glocker
2024	A*	`conf`	Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention. NeurIPS Avinash Kori, Francesco Locatello, Ainkaran Santhirasekaram, Francesca Toni, Ben Glocker, Fabio De Sousa Ribeiro
2024	J	`jnl`	Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention. CoRR Avinash Kori, Francesco Locatello, Ainkaran Santhirasekaram, Francesca Toni, Ben Glocker, Fabio De Sousa Ribeiro
2024	A*	`conf`	Identifying General Mechanism Shifts in Linear Causal Representations. NeurIPS Tianyu Chen, Kevin Bello, Francesco Locatello, Bryon Aragam, Pradeep Ravikumar
2024	J	`jnl`	Identifying General Mechanism Shifts in Linear Causal Representations. CoRR Tianyu Chen, Kevin Bello, Francesco Locatello, Bryon Aragam, Pradeep Ravikumar
2024	J	`jnl`	Latent Functional Maps. CoRR Marco Fumero, Marco Pegoraro, Valentino Maiorca, Francesco Locatello, Emanuele Rodolà
2024	A*	`conf`	Latent Functional Maps: a spectral framework for representation alignment. NeurIPS Marco Fumero, Marco Pegoraro, Valentino Maiorca, Francesco Locatello, Emanuele Rodolà
2024	J	`jnl`	Latent Space Translation via Inverse Relative Projection. CoRR Valentino Maiorca, Luca Moschella, Marco Fumero, Francesco Locatello, Emanuele Rodolà
2024	J	`jnl`	Look Around and Find Out: OOD Detection with Relative Angles. CoRR Berker Demirel, Marco Fumero, Francesco Locatello
2024	A*	`conf`	Marrying Causal Representation Learning with Dynamical Systems for Science. NeurIPS Dingling Yao, Caroline Muller, Francesco Locatello
2024	J	`jnl`	Marrying Causal Representation Learning with Dynamical Systems for Science. CoRR Dingling Yao, Caroline Muller, Francesco Locatello
2024	A*	`conf`	Mechanistic Neural Networks for Scientific Machine Learning. ICML Adeel Pervez, Francesco Locatello, Stratis Gavves
2024	J	`jnl`	Mechanistic Neural Networks for Scientific Machine Learning. CoRR Adeel Pervez, Francesco Locatello, Efstratios Gavves
2024	A*	`conf`	Multi-View Causal Representation Learning with Partial Observability. ICLR Dingling Yao, Danru Xu, Sébastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kügelgen, Francesco Locatello
2024	J	`jnl`	NeCo: Improving DINOv2's spatial representations in 19 GPU hours with Patch Neighbor Consistency. CoRR Valentinos Pariza, Mohammadreza Salehi, Gertjan J. Burghouts, Francesco Locatello, Yuki M. Asano
2024	J	`jnl`	ResiDual Transformer Alignment with Spectral Decomposition. CoRR Lorenzo Basile, Valentino Maiorca, Luca Bortolussi, Emanuele Rodolà, Francesco Locatello
2024	J	`jnl`	Scalable Mechanistic Neural Networks. CoRR Jiale Chen, Dingling Yao, Adeel Pervez, Dan Alistarh, Francesco Locatello
2024	J	`jnl`	Scalable unsupervised alignment of general metric and non-metric structures. CoRR Sanketh Vedula, Valentino Maiorca, Lorenzo Basile, Francesco Locatello, Alexander M. Bronstein
2024	J	`jnl`	Score matching through the roof: linear, nonlinear, and latent variables causal discovery. CoRR Francesco Montagna, Philipp Michael Faller, Patrick Blöbaum, Elke Kirschbaum, Francesco Locatello
2024	A	`conf`	Self-Compatibility: Evaluating Causal Discovery without Ground Truth. AISTATS Philipp Michael Faller, Leena C. Vankadara, Atalanti-Anastasia Mastakouri, Francesco Locatello, Dominik Janzing
2024	A*	`conf`	Smoke and Mirrors in Causal Downstream Tasks. NeurIPS Riccardo Cadei, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, Francesco Locatello
2024	J	`jnl`	Smoke and Mirrors in Causal Downstream Tasks. CoRR Riccardo Cadei, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, Francesco Locatello
2024	J	`jnl`	Two Tricks to Improve Unsupervised Segmentation Learning. CoRR Alp Eren Sari, Francesco Locatello, Paolo Favaro
2024	J	`jnl`	Unifying Causal Representation Learning with the Invariance Principle. CoRR Dingling Yao, Dario Rancati, Riccardo Cadei, Marco Fumero, Francesco Locatello
2024	A*	`conf`	Unsupervised Concept Discovery Mitigates Spurious Correlations. ICML Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi
2024	J	`jnl`	Unsupervised Concept Discovery Mitigates Spurious Correlations. CoRR Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi
2023	J	`jnl`	A data augmentation perspective on diffusion models and retrieval. CoRR Max F. Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell
2023	A*	`conf`	ASIF: Coupled Data Turns Unimodal Models to Multimodal without Training. NeurIPS Antonio Norelli, Marco Fumero, Valentino Maiorca, Luca Moschella, Emanuele Rodolà, Francesco Locatello
2023	A*	`conf`	Assumption violations in causal discovery and the robustness of score matching. NeurIPS Francesco Montagna, Atalanti-Anastasia Mastakouri, Elias Eulig, Nicoletta Noceti, Lorenzo Rosasco, Dominik Janzing, Bryon Aragam, Francesco Locatello
2023	J	`jnl`	Assumption violations in causal discovery and the robustness of score matching. CoRR Francesco Montagna, Atalanti-Anastasia Mastakouri, Elias Eulig, Nicoletta Noceti, Lorenzo Rosasco, Dominik Janzing, Bryon Aragam, Francesco Locatello
2023	A*	`conf`	Benign Overfitting in Deep Neural Networks under Lazy Training. ICML Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Francesco Locatello, Volkan Cevher
2023	J	`jnl`	Benign Overfitting in Deep Neural Networks under Lazy Training. CoRR Zhenyu Zhu, Fanghui Liu, Grigorios G. Chrysos, Francesco Locatello, Volkan Cevher
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	—	`conf`	Causal Discovery with Score Matching on Additive Models with Arbitrary Noise. CLeaR Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello
2023	J	`jnl`	Causal Discovery with Score Matching on Additive Models with Arbitrary Noise. CoRR Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello
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	J	`jnl`	Divided Attention: Unsupervised Multi-Object Discovery with Contextually Separated Slots. CoRR Dong Lao, Zhengyang Hu, Francesco Locatello, Yanchao Yang, Stefano Soatto
2023	J	`jnl`	Image retrieval outperforms diffusion models on data augmentation. Trans. Mach. Learn. Res. Max F. Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell
2023	A*	`conf`	Latent Space Translation via Semantic Alignment. NeurIPS Valentino Maiorca, Luca Moschella, Antonio Norelli, Marco Fumero, Francesco Locatello, Emanuele Rodolà
2023	J	`jnl`	Latent Space Translation via Semantic Alignment. CoRR Valentino Maiorca, Luca Moschella, Antonio Norelli, Marco Fumero, Francesco Locatello, Emanuele Rodolà
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	J	`jnl`	Multi-View Causal Representation Learning with Partial Observability. CoRR Dingling Yao, Danru Xu, Sébastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kügelgen, Francesco Locatello
2023	A*	`conf`	Object-Centric Multiple Object Tracking. ICCV Zixu Zhao, Jiaze Wang, Max Horn, Yizhuo Ding, Tong He, Zechen Bai, Dominik Zietlow, Carl-Johann Simon-Gabriel, Bing Shuai, Zhuowen Tu, Thomas Brox, Bernt Schiele, Yanwei Fu, Francesco Locatello, Zheng Zhang, Tianjun Xiao
2023	J	`jnl`	Object-Centric Multiple Object Tracking. CoRR Zixu Zhao, Jiaze Wang, Max Horn, Yizhuo Ding, Tong He, Zechen Bai, Dominik Zietlow, Carl-Johann Simon-Gabriel, Bing Shuai, Zhuowen Tu, Thomas Brox, Bernt Schiele, Yanwei Fu, Francesco Locatello, Zheng Zhang, Tianjun Xiao
2023	—	`conf`	Preface of UniReps: the First Workshop on Unifying Representations in Neural Models. UniReps Marco Fumero, Emanuele Rodolà, Clémentine C. J. Dominé, Francesco Locatello, Karolina Dziugaite, Mathilde Caron
2023	—	`ed.`	Proceedings of UniReps: the First Workshop on Unifying Representations in Neural Models, 15 December 2023, Ernest N. Morial Convention Center, New Orleans, USA. UniReps Marco Fumero, Emanuele Rodolà, Clémentine C. J. Dominé, Francesco Locatello, Karolina Dziugaite, Mathilde Caron
2023	A*	`conf`	Relative representations enable zero-shot latent space communication. ICLR Luca Moschella, Valentino Maiorca, Marco Fumero, Antonio Norelli, Francesco Locatello, Emanuele Rodolà
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	A*	`conf`	Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling. NeurIPS Zhenyu Zhu, Francesco Locatello, Volkan Cevher
2023	J	`jnl`	Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling. CoRR Zhenyu Zhu, Francesco Locatello, Volkan Cevher
2023	—	`conf`	Scalable Causal Discovery with Score Matching. CLeaR Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello
2023	J	`jnl`	Scalable Causal Discovery with Score Matching. CoRR Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello
2023	J	`jnl`	Self-Compatibility: Evaluating Causal Discovery without Ground Truth. CoRR Philipp Michael Faller, Leena Chennuru Vankadara, Atalanti-Anastasia Mastakouri, Francesco Locatello, Dominik Janzing
2023	J	`jnl`	Shortcuts for causal discovery of nonlinear models by score matching. CoRR Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Francesco Locatello
2023	A	`conf`	TeST: Test-time Self-Training under Distribution Shift. WACV Samarth Sinha, Peter V. Gehler, Francesco Locatello, Bernt Schiele
2023	J	`jnl`	Unsupervised Conditional Slot Attention for Object Centric Learning. CoRR Avinash Kori, Francesco Locatello, Francesca Toni, Ben Glocker
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	A*	`conf`	Unsupervised Open-Vocabulary Object Localization in Videos. ICCV Ke Fan, Zechen Bai, Tianjun Xiao, Dominik Zietlow, Max Horn, Zixu Zhao, Carl-Johann Simon-Gabriel, Mike Zheng Shou, Francesco Locatello, Bernt Schiele, Thomas Brox, Zheng Zhang, Yanwei Fu, Tong He
2023	J	`jnl`	Unsupervised Open-Vocabulary Object Localization in Videos. CoRR Ke Fan, Zechen Bai, Tianjun Xiao, Dominik Zietlow, Max Horn, Zixu Zhao, Carl-Johann Simon-Gabriel, Mike Zheng Shou, Francesco Locatello, Bernt Schiele, Thomas Brox, Zheng Zhang, Yanwei Fu, Tong He
2023	A*	`conf`	Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations. ICLR Andrii Zadaianchuk, Matthäus Kleindessner, Yi Zhu, Francesco Locatello, Thomas Brox
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	J	`jnl`	ASIF: Coupled Data Turns Unimodal Models to Multimodal Without Training. CoRR Antonio Norelli, Marco Fumero, Valentino Maiorca, Luca Moschella, Emanuele Rodolà, Francesco Locatello
2022	A*	`conf`	Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks. NeurIPS Michael Lohaus, Matthäus Kleindessner, Krishnaram Kenthapadi, Francesco Locatello, Chris Russell
2022	J	`jnl`	Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks. CoRR Michael Lohaus, Matthäus Kleindessner, Krishnaram Kenthapadi, Francesco Locatello, Chris Russell
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	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	J	`jnl`	Compositional Multi-Object Reinforcement Learning with Linear Relation Networks. CoRR Davide Mambelli, Frederik Träuble, Stefan Bauer, Bernhard Schölkopf, Francesco Locatello
2022	A	`conf`	Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization. AISTATS Gideon Dresdner, Maria-Luiza Vladarean, Gunnar Rätsch, Francesco Locatello, Volkan Cevher, Alp Yurtsever
2022	J	`jnl`	Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization. CoRR Gideon Dresdner, Maria-Luiza Vladarean, Gunnar Rätsch, Francesco Locatello, Volkan Cevher, Alp Yurtsever
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`	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	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`	Relative representations enable zero-shot latent space communication. CoRR Luca Moschella, Valentino Maiorca, Marco Fumero, Antonio Norelli, Francesco Locatello, Emanuele Rodolà
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`	Self-supervised Amodal Video Object Segmentation. NeurIPS Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello, David P. Wipf, Yanwei Fu, Zheng Zhang
2022	J	`jnl`	Self-supervised Amodal Video Object Segmentation. CoRR Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello, David Wipf, Yanwei Fu, Zheng Zhang
2022	J	`jnl`	TeST: Test-time Self-Training under Distribution Shift. CoRR Samarth Sinha, Peter V. Gehler, Francesco Locatello, Bernt Schiele
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	J	`jnl`	Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations. CoRR Andrii Zadaianchuk, Matthäus Kleindessner, Yi Zhu, Francesco Locatello, Thomas Brox
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`	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	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`	Boosting Variational Inference With Locally Adaptive Step-Sizes. IJCAI Gideon Dresdner, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, Gunnar Rätsch
2021	J	`jnl`	Boosting Variational Inference With Locally Adaptive Step-Sizes. CoRR Gideon Dresdner, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, Gunnar Rätsch
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	J	`jnl`	Enforcing and Discovering Structure in Machine Learning. CoRR Francesco Locatello
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`	Neighborhood Contrastive Learning Applied to Online Patient Monitoring. ICML Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch
2021	J	`jnl`	Neighborhood Contrastive Learning Applied to Online Patient Monitoring. CoRR Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch
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	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	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	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`	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`	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	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	A*	`conf`	Disentangling Factors of Variations Using Few Labels. ICLR Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem
2020	—	`—`	Enforcing and Discovering Structure in Machine Learning. Francesco Locatello
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	A*	`conf`	Object-Centric Learning with Slot Attention. NeurIPS Francesco Locatello, Dirk Weissenborn, Thomas Unterthiner, Aravindh Mahendran, Georg Heigold, Jakob Uszkoreit, Alexey Dosovitskiy, Thomas Kipf
2020	J	`jnl`	Object-Centric Learning with Slot Attention. CoRR Francesco Locatello, Dirk Weissenborn, Thomas Unterthiner, Aravindh Mahendran, Georg Heigold, Jakob Uszkoreit, Alexey Dosovitskiy, Thomas Kipf
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	J	`jnl`	SCIM: universal single-cell matching with unpaired feature sets. Bioinform. Stefan G. Stark, Joanna Ficek, Francesco Locatello, Ximena Bonilla, Stéphane Chevrier, Franziska Singer, Tumor Profiler Consortium, Gunnar Rätsch, Kjong-Van Lehmann
2020	A*	`conf`	Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization. ICML Geoffrey Négiar, Gideon Dresdner, Alicia Y. Tsai, Laurent El Ghaoui, Francesco Locatello, Robert Freund, Fabian Pedregosa
2020	J	`jnl`	Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization. CoRR Geoffrey Négiar, Gideon Dresdner, Alicia Y. Tsai, Laurent El Ghaoui, Francesco Locatello, Fabian Pedregosa
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
2019	A*	`conf`	Are Disentangled Representations Helpful for Abstract Visual Reasoning? NeurIPS Sjoerd van Steenkiste, Francesco Locatello, Jürgen Schmidhuber, Olivier Bachem
2019	J	`jnl`	Are Disentangled Representations Helpful for Abstract Visual Reasoning? CoRR Sjoerd van Steenkiste, Francesco Locatello, Jürgen Schmidhuber, Olivier Bachem
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`	Disentangling Factors of Variation Using Few Labels. CoRR Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem
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	—	`conf`	SOM-VAE: Interpretable Discrete Representation Learning on Time Series. ICLR (Poster) Vincent Fortuin, Matthias Hüser, Francesco Locatello, Heiko Strathmann, Gunnar Rätsch
2019	J	`jnl`	Stochastic Conditional Gradient Method for Composite Convex Minimization. CoRR Francesco Locatello, Alp Yurtsever, Olivier Fercoq, Volkan Cevher
2019	A*	`conf`	Stochastic Frank-Wolfe for Composite Convex Minimization. NeurIPS Francesco Locatello, Alp Yurtsever, Olivier Fercoq, Volkan Cevher
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
2018	A*	`conf`	A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming. ICML Alp Yurtsever, Olivier Fercoq, Francesco Locatello, Volkan Cevher
2018	A*	`conf`	Boosting Black Box Variational Inference. NeurIPS Francesco Locatello, Gideon Dresdner, Rajiv Khanna, Isabel Valera, Gunnar Rätsch
2018	J	`jnl`	Boosting Black Box Variational Inference. CoRR Francesco Locatello, Gideon Dresdner, Rajiv Khanna, Isabel Valera, Gunnar Rätsch
2018	A	`conf`	Boosting Variational Inference: an Optimization Perspective. AISTATS Francesco Locatello, Rajiv Khanna, Joydeep Ghosh, Gunnar Rätsch
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`	Deep Self-Organization: Interpretable Discrete Representation Learning on Time Series. CoRR Vincent Fortuin, Matthias Hüser, Francesco Locatello, Heiko Strathmann, Gunnar Rätsch
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`	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
2017	A	`conf`	A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe. AISTATS Francesco Locatello, Rajiv Khanna, Michael Tschannen, Martin Jaggi
2017	J	`jnl`	A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe. CoRR Francesco Locatello, Rajiv Khanna, Michael Tschannen, Martin Jaggi
2017	J	`jnl`	Boosting Variational Inference: an Optimization Perspective. CoRR Francesco Locatello, Rajiv Khanna, Joydeep Ghosh, Gunnar Rätsch
2017	—	`conf`	Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees. NIPS Francesco Locatello, Michael Tschannen, Gunnar Rätsch, Martin Jaggi
2017	J	`jnl`	Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees. CoRR Francesco Locatello, Michael Tschannen, Gunnar Rätsch, Martin Jaggi