Philippe Brouillard

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 9

Top Topics

Observational Data

Machine Learning

Causal Discovery

Inductive Inference

Top Venues

Publications

Julia Kaltenborn, Charlotte E. E. Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning. CoRR (2023)
Julia Kaltenborn, Charlotte E. E. Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning. NeurIPS (2023)
Julien Boussard, Chandni Nagda, Julia Kaltenborn, Charlotte Emilie Elektra Lange, Philippe Brouillard, Yaniv Gurwicz, Peer Nowack, David Rolnick
Towards Causal Representations of Climate Model Data. CoRR (2023)
Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin
Typing assumptions improve identification in causal discovery. CLeaR (2022)
Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin
Typing assumptions improve identification in causal discovery. CoRR (2021)
Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
Differentiable Causal Discovery from Interventional Data. NeurIPS (2020)
Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien
Gradient-Based Neural DAG Learning. ICLR (2020)
Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
Differentiable Causal Discovery from Interventional Data. CoRR (2020)
Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien
Gradient-Based Neural DAG Learning. CoRR (2019)