Sébastien Lachapelle | DeepAI

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∙ 07/05/2023

Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation

We tackle the problems of latent variables identification and "out-of-su...

0 Sébastien Lachapelle, et al. ∙

∙ 11/26/2022

Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective

Although disentangled representations are often said to be beneficial fo...

0 Sébastien Lachapelle, et al. ∙

∙ 07/15/2022

Partial Disentanglement via Mechanism Sparsity

Disentanglement via mechanism sparsity was introduced recently as a prin...

9 Sébastien Lachapelle, et al. ∙

∙ 07/22/2021

Typing assumptions improve identification in causal discovery

Causal discovery from observational data is a challenging task to which ...

10 Philippe Brouillard, et al. ∙

∙ 07/21/2021

Discovering Latent Causal Variables via Mechanism Sparsity: A New Principle for Nonlinear ICA

It can be argued that finding an interpretable low-dimensional represent...

23 Sébastien Lachapelle, et al. ∙

∙ 11/23/2020

On the Convergence of Continuous Constrained Optimization for Structure Learning

Structure learning of directed acyclic graphs (DAGs) is a fundamental pr...

0 Ignavier Ng, et al. ∙

∙ 07/03/2020

Differentiable Causal Discovery from Interventional Data

Discovering causal relationships in data is a challenging task that invo...

6 Philippe Brouillard, et al. ∙

∙ 06/05/2019

Gradient-Based Neural DAG Learning

We propose a novel score-based approach to learning a directed acyclic g...

3 Sébastien Lachapelle, et al. ∙

∙ 01/30/2019

A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms

We propose to meta-learn causal structures based on how fast a learner a...

0 Yoshua Bengio, et al. ∙

∙ 01/22/2019

Predicting Tactical Solutions to Operational Planning Problems under Imperfect Information

This paper offers a methodological contribution at the intersection of m...

14 Eric Larsen, et al. ∙

∙ 07/31/2018

Predicting Solution Summaries to Integer Linear Programs under Imperfect Information with Machine Learning

The paper provides a methodological contribution at the intersection of ...

2 Eric Larsen, et al. ∙

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