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ORCIDSébastien Lachapelle
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Journal Articles
- 2022
[j1]Eric Larsen
, Sébastien Lachapelle, Yoshua Bengio, Emma Frejinger, Simon Lacoste-Julien, Andrea Lodi:
Predicting Tactical Solutions to Operational Planning Problems Under Imperfect Information. INFORMS J. Comput. 34(1): 227-242 (2022)
Conference and Workshop Papers
- 2024
- [c10]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 - [c9]Danru Xu, Dingling Yao, Sébastien Lachapelle, Perouz Taslakian, Julius von Kügelgen, Francesco Locatello, Sara Magliacane:
A Sparsity Principle for Partially Observable Causal Representation Learning. ICML 2024 - 2023
- [c8]Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand:
Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning. ICML 2023: 18171-18206 - [c7]Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien:
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation. NeurIPS 2023 - 2022
- [c6]Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, Kun Zhang:
On the Convergence of Continuous Constrained Optimization for Structure Learning. AISTATS 2022: 8176-8198 - [c5]Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin:
Typing assumptions improve identification in causal discovery. CLeaR 2022: 162-177 - [c4]Sébastien Lachapelle, Pau Rodríguez, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien:
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA. CLeaR 2022: 428-484 - 2020
- [c3]Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal:
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. ICLR 2020 - [c2]Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien:
Gradient-Based Neural DAG Learning. ICLR 2020 - [c1]Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin:
Differentiable Causal Discovery from Interventional Data. NeurIPS 2020
Informal and Other Publications
- 2024
- [i14]Sébastien Lachapelle, Pau Rodríguez López, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien:
Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies. CoRR abs/2401.04890 (2024) - [i13]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 abs/2403.08335 (2024) - [i12]Elliot Layne, Jason S. Hartford, Sébastien Lachapelle, Mathieu Blanchette, Dhanya Sridhar:
Leveraging Structure Between Environments: Phylogenetic Regularization Incentivizes Disentangled Representations. CoRR abs/2405.20482 (2024) - 2023
- [i11]Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien:
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation. CoRR abs/2307.02598 (2023) - [i10]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 abs/2311.04056 (2023) - 2022
- [i9]Sébastien Lachapelle, Simon Lacoste-Julien:
Partial Disentanglement via Mechanism Sparsity. CoRR abs/2207.07732 (2022) - [i8]Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand:
Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective. CoRR abs/2211.14666 (2022) - 2021
- [i7]Sébastien Lachapelle, Pau Rodríguez López, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien:
Discovering Latent Causal Variables via Mechanism Sparsity: A New Principle for Nonlinear ICA. CoRR abs/2107.10098 (2021) - [i6]Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin:
Typing assumptions improve identification in causal discovery. CoRR abs/2107.10703 (2021) - 2020
- [i5]Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin:
Differentiable Causal Discovery from Interventional Data. CoRR abs/2007.01754 (2020) - [i4]Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien:
On the Convergence of Continuous Constrained Optimization for Structure Learning. CoRR abs/2011.11150 (2020) - 2019
- [i3]Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal:
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. CoRR abs/1901.10912 (2019) - [i2]Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien:
Gradient-Based Neural DAG Learning. CoRR abs/1906.02226 (2019) - 2018
- [i1]Eric Larsen, Sébastien Lachapelle, Yoshua Bengio, Emma Frejinger, Simon Lacoste-Julien, Andrea Lodi:
Predicting Solution Summaries to Integer Linear Programs under Imperfect Information with Machine Learning. CoRR abs/1807.11876 (2018)
Coauthor Index
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