Sébastien Lachapelle

Publications

Learning a Spatial Partitioning and its Causal Relations from Temporal Data. Philippe Brouillard, Sébastien Lachapelle, Julia Kaltenborn, Yaniv Gurwicz, Dhanya Sridhar, Alexandre Drouin, Peer Nowack, Jakob Runge, David Rolnick. At Causal Learning and Reasoning (CLeaR), 2026.

Article Citation

A Sparsity Principle for Partially Observable Causal Representation Learning. Danru Xu, Dingling Yao, Sébastien Lachapelle, Perouz Taslakian, Sara Magliacane, Francesco Locatello, Julius von Kügelgen. At International Conference on Machine Learning (ICML), 2024.

Article Citation Code

Multi-View Causal Representation Learning with Partial Observability. Dingling Yao, Danru Xu, Perouz Taslakian, Sébastien Lachapelle, Sara Magliacane, Julius von Kügelgen, Francesco Locatello. At International Conference of Learning Representations (ICLR), 2024.

Article Citation Code

A Sparsity Principle for Partially Observable Causal. Danru Xu, Dingling Yao, Perouz Taslakian, Sébastien Lachapelle, Julius von Kügelgen, Francesco Locatello, Sara Magliacane. At Workshop at the Neural Information Processing Systems (NeurIPS), 2023.

Article Citation

Multi-View Causal Representation Learning with Partial Observability. Dingling Yao, Danru Xu, Perouz Taslakian, Sébastien Lachapelle, Sara Magliacane, Julius von Kügelgen, Francesco Locatello. At Workshop at the Neural Information Processing Systems (NeurIPS), 2023.

Article Citation

Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA. Sébastien Lachapelle, Pau Rodriguez, Yash Sharma, Katie Everett , Rémi Le Priol, Alexandre Lacoste, Simon Lcoste-Julien. At Causal Learning and Reasoning (CLeaR), 2022.

Article Citation Code

Typing assumptions improve identification in causal discovery - theory and algorithms. Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin. At Causal Learning and Reasoning (CLeaR), 2022.

Article Citation Code

Typing assumptions improve identification in causal discovery - Report and comments on future directions. Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin. At Workshop at the Neural Information Processing Systems (NeurIPS), 2021.

Article Citation Code

Typing assumptions improve identification in causal discovery. Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin. At Workshop at the International Conference on Machine Learning (ICML), 2021.

Article Citation Code

Differentiable Causal Discovery from Interventional Data. Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lcoste-Julien, Alexandre Drouin. At Conference on Neural Information Processing Systems (NeurIPS), 2020.

Article Citation Code Vidéo

A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher Pal. At International Conference on Learning Representations (ICLR), 2020.

Article Citation Code Vidéo

Gradient-Based Neural DAG Learning with Interventions. Philippe Brouillard, Alexandre Drouin, Sébastien Lachapelle, Alexandre Lacoste, Simon Lcoste-Julien. At Workshop at the International Conference on Learning Representations (ICLR), 2020.

Article Citation Code Vidéo