Sébastien Lachapelle
Sébastien Lachapelle
PhD Student, Mila, Université de Montréal
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Zitiert von
Zitiert von
A meta-transfer objective for learning to disentangle causal mechanisms
Y Bengio, T Deleu, N Rahaman, R Ke, S Lachapelle, O Bilaniuk, A Goyal, ...
arXiv preprint arXiv:1901.10912, 2019
Gradient-based neural dag learning
S Lachapelle, P Brouillard, T Deleu, S Lacoste-Julien
arXiv preprint arXiv:1906.02226, 2019
Differentiable causal discovery from interventional data
P Brouillard, S Lachapelle, A Lacoste, S Lacoste-Julien, A Drouin
Advances in Neural Information Processing Systems 33, 21865-21877, 2020
Predicting tactical solutions to operational planning problems under imperfect information
E Larsen, S Lachapelle, Y Bengio, E Frejinger, S Lacoste-Julien, A Lodi
INFORMS Journal on Computing 34 (1), 227-242, 2022
Disentanglement via mechanism sparsity regularization: A new principle for nonlinear ICA
S Lachapelle, P Rodriguez, Y Sharma, KE Everett, R Le Priol, A Lacoste, ...
Conference on Causal Learning and Reasoning, 428-484, 2022
On the convergence of continuous constrained optimization for structure learning
I Ng, S Lachapelle, NR Ke, S Lacoste-Julien, K Zhang
International Conference on Artificial Intelligence and Statistics, 8176-8198, 2022
Typing assumptions improve identification in causal discovery
P Brouillard, P Taslakian, A Lacoste, S Lachapelle, A Drouin
Conference on Causal Learning and Reasoning, 162-177, 2022
Partial Disentanglement via Mechanism Sparsity
S Lachapelle, S Lacoste-Julien
arXiv preprint arXiv:2207.07732, 2022
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