Francesco Locatello

ORCID

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 140

Top Venues

Publications

Dingling Yao, Danru Xu, Sébastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kügelgen, Francesco Locatello
Multi-View Causal Representation Learning with Partial Observability. ICLR (2024)
Marco Fumero, Marco Pegoraro, Valentino Maiorca, Francesco Locatello, Emanuele Rodolà
Latent Functional Maps. CoRR (2024)
Philipp Michael Faller, Leena C. Vankadara, Atalanti-Anastasia Mastakouri, Francesco Locatello, Dominik Janzing
Self-Compatibility: Evaluating Causal Discovery without Ground Truth. AISTATS (2024)
Riccardo Cadei, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, Francesco Locatello
Smoke and Mirrors in Causal Downstream Tasks. CoRR (2024)
Francesco Montagna, Max Cairney-Leeming, Dhanya Sridhar, Francesco Locatello
Demystifying amortized causal discovery with transformers. CoRR (2024)
Sanketh Vedula, Valentino Maiorca, Lorenzo Basile, Francesco Locatello, Alexander M. Bronstein
Scalable unsupervised alignment of general metric and non-metric structures. CoRR (2024)
Ke Fan, Zechen Bai, Tianjun Xiao, Tong He, Max Horn, Yanwei Fu, Francesco Locatello, Zheng Zhang
Adaptive Slot Attention: Object Discovery with Dynamic Slot Number. CoRR (2024)
Adeel Pervez, Francesco Locatello, Efstratios Gavves
Mechanistic Neural Networks for Scientific Machine Learning. CoRR (2024)
Francesco Montagna, Philipp Michael Faller, Patrick Blöbaum, Elke Kirschbaum, Francesco Locatello
Score matching through the roof: linear, nonlinear, and latent variables causal discovery. CoRR (2024)
Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi
Unsupervised Concept Discovery Mitigates Spurious Correlations. CoRR (2024)
Sindy Löwe, Francesco Locatello, Max Welling
Binding Dynamics in Rotating Features. CoRR (2024)
Valentino Maiorca, Luca Moschella, Marco Fumero, Francesco Locatello, Emanuele Rodolà
Latent Space Translation via Inverse Relative Projection. CoRR (2024)
Dingling Yao, Caroline Muller, Francesco Locatello
Marrying Causal Representation Learning with Dynamical Systems for Science. CoRR (2024)
Danru Xu, Dingling Yao, Sébastien Lachapelle, Perouz Taslakian, Julius von Kügelgen, Francesco Locatello, Sara Magliacane
A Sparsity Principle for Partially Observable Causal Representation Learning. CoRR (2024)
Alp Eren Sari, Francesco Locatello, Paolo Favaro
Two Tricks to Improve Unsupervised Segmentation Learning. CoRR (2024)
Avinash Kori, Francesco Locatello, Fabio De Sousa Ribeiro, Francesca Toni, Ben Glocker
Grounded Object-Centric Learning. ICLR (2024)
Avinash Kori, Francesco Locatello, Ainkaran Santhirasekaram, Francesca Toni, Ben Glocker, Fabio De Sousa Ribeiro
Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention. CoRR (2024)
Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, Francesco Locatello
Bridging the Gap to Real-World Object-Centric Learning. ICLR (2023)
Dingling Yao, Danru Xu, Sébastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kügelgen, Francesco Locatello
Multi-View Causal Representation Learning with Partial Observability. CoRR (2023)
Marco Fumero, Emanuele Rodolà, Clémentine Dominé, Francesco Locatello, Karolina Dziugaite, Mathilde Caron
Preface of UniReps: the First Workshop on Unifying Representations in Neural Models. UniReps (2023)
Max F. Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell
A data augmentation perspective on diffusion models and retrieval. CoRR (2023)
Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello
Scalable Causal Discovery with Score Matching. CLeaR (2023)
Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
Leveraging sparse and shared feature activations for disentangled representation learning. CoRR (2023)
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
Unsupervised Open-Vocabulary Object Localization in Videos. ICCV (2023)
Sindy Löwe, Phillip Lippe, Francesco Locatello, Max Welling
Rotating Features for Object Discovery. CoRR (2023)
Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
Leveraging sparse and shared feature activations for disentangled representation learning. NeurIPS (2023)
Francesco Montagna, Atalanti-Anastasia Mastakouri, Elias Eulig, Nicoletta Noceti, Lorenzo Rosasco, Dominik Janzing, Bryon Aragam, Francesco Locatello
Assumption violations in causal discovery and the robustness of score matching. CoRR (2023)
Zhenyu Zhu, Francesco Locatello, Volkan Cevher
Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling. NeurIPS (2023)
Luca Moschella, Valentino Maiorca, Marco Fumero, Antonio Norelli, Francesco Locatello, Emanuele Rodolà
Relative representations enable zero-shot latent space communication. ICLR (2023)
Valentino Maiorca, Luca Moschella, Antonio Norelli, Marco Fumero, Francesco Locatello, Emanuele Rodolà
Latent Space Translation via Semantic Alignment. NeurIPS (2023)
Antonio Norelli, Marco Fumero, Valentino Maiorca, Luca Moschella, Emanuele Rodolà, Francesco Locatello
ASIF: Coupled Data Turns Unimodal Models to Multimodal without Training. NeurIPS (2023)
Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello
Scalable Causal Discovery with Score Matching. CoRR (2023)
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
Object-Centric Multiple Object Tracking. CoRR (2023)
Yuejiang Liu, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning. CLeaR (2023)
Max F. Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell
Image retrieval outperforms diffusion models on data augmentation. Trans. Mach. Learn. Res. 2023 (2023)
Andrii Zadaianchuk, Matthäus Kleindessner, Yi Zhu, Francesco Locatello, Thomas Brox
Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations. ICLR (2023)
Zhenyu Zhu, Francesco Locatello, Volkan Cevher
Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling. CoRR (2023)
Zhenyu Zhu, Fanghui Liu, Grigorios G. Chrysos, Francesco Locatello, Volkan Cevher
Benign Overfitting in Deep Neural Networks under Lazy Training. CoRR (2023)
Yuejiang Liu, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning. CoRR (2023)
Francesco Montagna, Atalanti-Anastasia Mastakouri, Elias Eulig, Nicoletta Noceti, Lorenzo Rosasco, Dominik Janzing, Bryon Aragam, Francesco Locatello
Assumption violations in causal discovery and the robustness of score matching. NeurIPS (2023)
Avinash Kori, Francesco Locatello, Francesca Toni, Ben Glocker
Unsupervised Conditional Slot Attention for Object Centric Learning. CoRR (2023)
Matthias Tangemann, Steffen Schneider, Julius von Kügelgen, Francesco Locatello, Peter Vincent Gehler, Thomas Brox, Matthias Kümmerer, Matthias Bethge, Bernhard Schölkopf
Unsupervised Object Learning via Common Fate. CLeaR (2023)
Sindy Löwe, Phillip Lippe, Francesco Locatello, Max Welling
Rotating Features for Object Discovery. NeurIPS (2023)
Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Francesco Locatello
Shortcuts for causal discovery of nonlinear models by score matching. CoRR (2023)
Samarth Sinha, Peter V. Gehler, Francesco Locatello, Bernt Schiele
TeST: Test-time Self-Training under Distribution Shift. WACV (2023)
Dong Lao, Zhengyang Hu, Francesco Locatello, Yanchao Yang, Stefano Soatto
Divided Attention: Unsupervised Multi-Object Discovery with Contextually Separated Slots. CoRR (2023)
Valentino Maiorca, Luca Moschella, Antonio Norelli, Marco Fumero, Francesco Locatello, Emanuele Rodolà
Latent Space Translation via Semantic Alignment. CoRR (2023)
Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Francesco Locatello, Volkan Cevher
Benign Overfitting in Deep Neural Networks under Lazy Training. ICML (2023)
Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise. CoRR (2023)
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
Object-Centric Multiple Object Tracking. ICCV (2023)
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
Unsupervised Open-Vocabulary Object Localization in Videos. CoRR (2023)
Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, Francesco Locatello
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise. CLeaR (2023)
Philipp Michael Faller, Leena Chennuru Vankadara, Atalanti-Anastasia Mastakouri, Francesco Locatello, Dominik Janzing
Self-Compatibility: Evaluating Causal Discovery without Ground Truth. CoRR (2023)
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
Assaying Out-Of-Distribution Generalization in Transfer Learning. NeurIPS (2022)
Antonio Norelli, Marco Fumero, Valentino Maiorca, Luca Moschella, Emanuele Rodolà, Francesco Locatello
ASIF: Coupled Data Turns Unimodal Models to Multimodal Without Training. CoRR (2022)
Gideon Dresdner, Maria-Luiza Vladarean, Gunnar Rätsch, Francesco Locatello, Volkan Cevher, Alp Yurtsever
Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization. CoRR (2022)
Michael Lohaus, Matthäus Kleindessner, Krishnaram Kenthapadi, Francesco Locatello, Chris Russell
Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks. NeurIPS (2022)
Gideon Dresdner, Maria-Luiza Vladarean, Gunnar Rätsch, Francesco Locatello, Volkan Cevher, Alp Yurtsever
Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization. AISTATS (2022)
Paul Rolland, Volkan Cevher, Matthäus Kleindessner, Chris Russell, Dominik Janzing, Bernhard Schölkopf, Francesco Locatello
Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models. ICML (2022)
Dominik Zietlow, Michael Lohaus, Guha Balakrishnan, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Chris Russell
Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers. CVPR (2022)
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
Assaying Out-Of-Distribution Generalization in Transfer Learning. CoRR (2022)
Paul Rolland, Volkan Cevher, Matthäus Kleindessner, Chris Russell, Bernhard Schölkopf, Dominik Janzing, Francesco Locatello
Score matching enables causal discovery of nonlinear additive noise models. CoRR (2022)
Lukas Schott, Julius von Kügelgen, Frederik Träuble, Peter Vincent Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain. ICLR (2022)
Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, Francesco Locatello
Bridging the Gap to Real-World Object-Centric Learning. CoRR (2022)
Michael Lohaus, Matthäus Kleindessner, Krishnaram Kenthapadi, Francesco Locatello, Chris Russell
Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks. CoRR (2022)
Andrea Dittadi, Samuele S. Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello
Generalization and Robustness Implications in Object-Centric Learning. ICML (2022)
Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello, David P. Wipf, Yanwei Fu, Zheng Zhang
Self-supervised Amodal Video Object Segmentation. NeurIPS (2022)
Andrii Zadaianchuk, Matthäus Kleindessner, Yi Zhu, Francesco Locatello, Thomas Brox
Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations. CoRR (2022)
Dominik Zietlow, Michael Lohaus, Guha Balakrishnan, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Chris Russell
Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers. CoRR (2022)
Nasim Rahaman, Martin Weiss, Frederik Träuble, Francesco Locatello, Alexandre Lacoste, Yoshua Bengio, Chris Pal, Li Erran Li, Bernhard Schölkopf
A General Purpose Neural Architecture for Geospatial Systems. CoRR (2022)
Luca Moschella, Valentino Maiorca, Marco Fumero, Antonio Norelli, Francesco Locatello, Emanuele Rodolà
Relative representations enable zero-shot latent space communication. CoRR (2022)
Nasim Rahaman, Martin Weiss, Francesco Locatello, Chris Pal, Yoshua Bengio, Bernhard Schölkopf, Li Erran Li, Nicolas Ballas
Neural Attentive Circuits. CoRR (2022)
Osama Makansi, Julius von Kügelgen, Francesco Locatello, Peter Vincent Gehler, Dominik Janzing, Thomas Brox, Bernhard Schölkopf
You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction. ICLR (2022)
Samarth Sinha, Peter V. Gehler, Francesco Locatello, Bernt Schiele
TeST: Test-time Self-Training under Distribution Shift. CoRR (2022)
Martin Weiss, Nasim Rahaman, Francesco Locatello, Chris Pal, Yoshua Bengio, Bernhard Schölkopf, Li Erran Li, Nicolas Ballas
Neural Attentive Circuits. NeurIPS (2022)
Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
The Role of Pretrained Representations for the OOD Generalization of RL Agents. ICLR (2022)
Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello, David Wipf, Yanwei Fu, Zheng Zhang
Self-supervised Amodal Video Object Segmentation. CoRR (2022)
Davide Mambelli, Frederik Träuble, Stefan Bauer, Bernhard Schölkopf, Francesco Locatello
Compositional Multi-Object Reinforcement Learning with Linear Relation Networks. CoRR (2022)
Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf
On the Transfer of Disentangled Representations in Realistic Settings. ICLR (2021)
Andrea Dittadi, Frederik Träuble, Manuel Wüthrich, Felix Widmaier, Peter V. Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning. CoRR (2021)
Andrea Dittadi, Samuele Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello
Generalization and Robustness Implications in Object-Centric Learning. CoRR (2021)
Lukas Schott, Julius von Kügelgen, Frederik Träuble, Peter V. Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain. CoRR (2021)
Gideon Dresdner, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, Gunnar Rätsch
Boosting Variational Inference With Locally Adaptive Step-Sizes. IJCAI (2021)
Gideon Dresdner, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, Gunnar Rätsch
Boosting Variational Inference With Locally Adaptive Step-Sizes. CoRR (2021)
Francesco Locatello
Enforcing and Discovering Structure in Machine Learning. CoRR (2021)
Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch
Neighborhood Contrastive Learning Applied to Online Patient Monitoring. ICML (2021)
Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter V. Gehler, Yoshua Bengio, Francesco Locatello, Bernhard Schölkopf
Dynamic Inference with Neural Interpreters. CoRR (2021)
Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, Francesco Locatello
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style. CoRR (2021)
Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio
Towards Causal Representation Learning. CoRR (2021)
Frederik Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Peter V. Gehler
Backward-Compatible Prediction Updates: A Probabilistic Approach. CoRR (2021)
Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter V. Gehler, Yoshua Bengio, Francesco Locatello, Bernhard Schölkopf
Dynamic Inference with Neural Interpreters. NeurIPS (2021)
Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch
Neighborhood Contrastive Learning Applied to Online Patient Monitoring. CoRR (2021)
Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer
On Disentangled Representations Learned from Correlated Data. ICML (2021)
Frederik Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Peter V. Gehler
Backward-Compatible Prediction Updates: A Probabilistic Approach. NeurIPS (2021)
Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio
Toward Causal Representation Learning. Proc. IEEE 109 (5) (2021)
Matthias Tangemann, Steffen Schneider, Julius von Kügelgen, Francesco Locatello, Peter V. Gehler, Thomas Brox, Matthias Kümmerer, Matthias Bethge, Bernhard Schölkopf
Unsupervised Object Learning via Common Fate. CoRR (2021)
Osama Makansi, Julius von Kügelgen, Francesco Locatello, Peter V. Gehler, Dominik Janzing, Thomas Brox, Bernhard Schölkopf
You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction. CoRR (2021)
Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, Francesco Locatello
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style. NeurIPS (2021)
Geoffrey Négiar, Gideon Dresdner, Alicia Y. Tsai, Laurent El Ghaoui, Francesco Locatello, Fabian Pedregosa
Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization. CoRR (2020)
Francesco Locatello, Dirk Weissenborn, Thomas Unterthiner, Aravindh Mahendran, Georg Heigold, Jakob Uszkoreit, Alexey Dosovitskiy, Thomas Kipf
Object-Centric Learning with Slot Attention. NeurIPS (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Francesco Locatello