Philippe Brouillard

Philippe Brouillard

PhD Candidate

Université de Montréal

MILA

Biography

I am Philippe Brouillard, a PhD student cosupervised by Dhanya Sridhar and Alexandre Drouin at the Université de Montréal (UdeM) and at Mila, the Quebec Artificial Intelligence Institute.

My research interests include causal discovery, causal representation learning, machine learning, and how to combine them!

Interests
  • Causal discovery
  • Causal representation learning
  • Machine learning
Education
  • PhD in Computer Science, 2025 (expected)

    UdeM

  • MSc in Computer Science, 2021

    UdeM

  • BSc in Mathematics, 2017

    UdeM

  • BSc in Psychology, 2014

    UQAM

Publications

(2025). The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications. In CLeaR 2025.

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(2023). Climateset: A large-scale climate model dataset for machine learning. In NeurIPS 2023 - Datasets and Benchmarks.

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(2022). Typing Assumptions Improve Identification in Causal Discovery. In CLeaR 2022.

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(2020). Differentiable Causal Discovery with Interventional Data. In NeurIPS 2020.

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(2020). Gradient-based Neural DAG Learning with Intervention. In Causal Learning for Decision Making workshop, ICLR 2020.

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(2020). Gradient-Based Neural DAG Learning. In ICLR 2020.

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