ML Anthology

Lachapelle, Sebastien

18 publications

AISTATS 2025 All or None: Identifiable Linear Properties of Next-Token Predictors in Language Modeling Emanuele Marconato, Sebastien Lachapelle, Sebastian Weichwald, Luigi Gresele
ICLR 2025 Interaction Asymmetry: A General Principle for Learning Composable Abstractions Jack Brady, Julius von Kügelgen, Sebastien Lachapelle, Simon Buchholz, Thomas Kipf, Wieland Brendel
TMLR 2025 Sparsity Regularization via Tree-Structured Environments for Disentangled Representations Elliot Layne, Jason Hartford, Sebastien Lachapelle, Mathieu Blanchette, Dhanya Sridhar
ICML 2024 A Sparsity Principle for Partially Observable Causal Representation Learning Danru Xu, Dingling Yao, Sebastien Lachapelle, Perouz Taslakian, Julius Von Kügelgen, Francesco Locatello, Sara Magliacane
NeurIPSW 2024 Interaction Asymmetry: A General Principle for Learning Composable Abstractions Jack Brady, Julius von Kügelgen, Sebastien Lachapelle, Simon Buchholz, Wieland Brendel
ICLR 2024 Multi-View Causal Representation Learning with Partial Observability Dingling Yao, Danru Xu, Sebastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kügelgen, Francesco Locatello
NeurIPSW 2024 Towards Object-Centric Learning with General Purpose Architectures Jack Brady, Julius von Kügelgen, Sebastien Lachapelle, Simon Buchholz, Thomas Kipf, Wieland Brendel
NeurIPSW 2023 A Sparsity Principle for Partially Observable Causal Representation Learning Danru Xu, Dingling Yao, Sebastien Lachapelle, Perouz Taslakian, Julius von Kügelgen, Francesco Locatello, Sara Magliacane
NeurIPS 2023 Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien
NeurIPSW 2023 Multi-View Causal Representation Learning with Partial Observability Dingling Yao, Danru Xu, Sebastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kügelgen, Francesco Locatello
ICML 2023 Synergies Between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning Sebastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand
AISTATS 2022 On the Convergence of Continuous Constrained Optimization for Structure Learning Ignavier Ng, Sebastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, Kun Zhang
CLeaR 2022 Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA Sebastien Lachapelle, Pau Rodriguez, Yash Sharma, Katie E Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
CLeaR 2022 Typing Assumptions Improve Identification in Causal Discovery Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sebastien Lachapelle, Alexandre Drouin
ICLR 2020 A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher Pal
NeurIPS 2020 Differentiable Causal Discovery from Interventional Data Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
ICLR 2020 Gradient-Based Neural DAG Learning Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien
NeurIPSW 2019 Gradient-Based Neural DAG Learning Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien