Sébastien Lachapelle

34 papers A* 8A 2Journal 22Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	On the Sample Efficiency of Inverse Dynamics Models for Semi-Supervised Imitation Learning. CoRR Sacha Morin, Moonsub Byeon, Alexia Jolicoeur-Martineau, Sébastien Lachapelle
2025	A	`conf`	All or None: Identifiable Linear Properties of Next-Token Predictors in Language Modeling. AISTATS Emanuele Marconato, Sébastien Lachapelle, Sebastian Weichwald, Luigi Gresele
2025	J	`jnl`	Identifiable Steering via Sparse Autoencoding of Multi-Concept Shifts. CoRR Shruti Joshi, Andrea Dittadi, Sébastien Lachapelle, Dhanya Sridhar
2025	A*	`conf`	Interaction Asymmetry: A General Principle for Learning Composable Abstractions. ICLR Jack Brady, Julius von Kügelgen, Sébastien Lachapelle, Simon Buchholz, Thomas Kipf, Wieland Brendel
2025	J	`jnl`	On the Identifiability of Latent Action Policies. CoRR Sébastien Lachapelle
2025	J	`jnl`	Sparsity regularization via tree-structured environments for disentangled representations. Trans. Mach. Learn. Res. Elliot Layne, Jason S. Hartford, Sébastien Lachapelle, Mathieu Blanchette, Dhanya Sridhar
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	J	`jnl`	All or None: Identifiable Linear Properties of Next-token Predictors in Language Modeling. CoRR Emanuele Marconato, Sébastien Lachapelle, Sebastian Weichwald, Luigi Gresele
2024	J	`jnl`	Causal Representation Learning in Temporal Data via Single-Parent Decoding. CoRR Philippe Brouillard, Sébastien Lachapelle, Julia Kaltenborn, Yaniv Gurwicz, Dhanya Sridhar, Alexandre Drouin, Peer Nowack, Jakob Runge, David Rolnick
2024	J	`jnl`	Interaction Asymmetry: A General Principle for Learning Composable Abstractions. CoRR Jack Brady, Julius von Kügelgen, Sébastien Lachapelle, Simon Buchholz, Thomas Kipf, Wieland Brendel
2024	J	`jnl`	Leveraging Structure Between Environments: Phylogenetic Regularization Incentivizes Disentangled Representations. CoRR Elliot Layne, Jason S. Hartford, Sébastien Lachapelle, Mathieu Blanchette, Dhanya Sridhar
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`	Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies. CoRR Sébastien Lachapelle, Pau Rodríguez López, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
2023	A*	`conf`	Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation. NeurIPS Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien
2023	J	`jnl`	Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation. CoRR Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien
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`	Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning. ICML Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand
2022	—	`conf`	Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA. CLeaR Sébastien Lachapelle, Pau Rodríguez, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
2022	A	`conf`	On the Convergence of Continuous Constrained Optimization for Structure Learning. AISTATS Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, Kun Zhang
2022	J	`jnl`	Partial Disentanglement via Mechanism Sparsity. CoRR Sébastien Lachapelle, Simon Lacoste-Julien
2022	J	`jnl`	Predicting Tactical Solutions to Operational Planning Problems Under Imperfect Information. INFORMS J. Comput. Eric Larsen, Sébastien Lachapelle, Yoshua Bengio, Emma Frejinger, Simon Lacoste-Julien, Andrea Lodi
2022	J	`jnl`	Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective. CoRR Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand
2022	—	`conf`	Typing assumptions improve identification in causal discovery. CLeaR Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin
2021	J	`jnl`	Discovering Latent Causal Variables via Mechanism Sparsity: A New Principle for Nonlinear ICA. CoRR Sébastien Lachapelle, Pau Rodríguez López, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
2021	J	`jnl`	Typing assumptions improve identification in causal discovery. CoRR Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin
2020	A*	`conf`	A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. ICLR Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal
2020	A*	`conf`	Differentiable Causal Discovery from Interventional Data. NeurIPS Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
2020	J	`jnl`	Differentiable Causal Discovery from Interventional Data. CoRR Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
2020	A*	`conf`	Gradient-Based Neural DAG Learning. ICLR Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien
2020	J	`jnl`	On the Convergence of Continuous Constrained Optimization for Structure Learning. CoRR Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien
2019	J	`jnl`	A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. CoRR Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal
2019	J	`jnl`	Gradient-Based Neural DAG Learning. CoRR Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien
2018	J	`jnl`	Predicting Solution Summaries to Integer Linear Programs under Imperfect Information with Machine Learning. CoRR Eric Larsen, Sébastien Lachapelle, Yoshua Bengio, Emma Frejinger, Simon Lacoste-Julien, Andrea Lodi