Tristan Deleu

Valence Labs · Recursion
Mila - Quebec Artificial Intelligence Institute · Université de Montréal


I am Senior Research Scientist at Valence Labs, Recursion, and a final year Ph.D. candidate at Mila & Université de Montréal, under the supervision of Yoshua Bengio. My research interests include Probabilistic Modeling, Structure Learning, Causal Discovery, Meta-Learning, and Reinforcement Learning. I received the Antidote Scholarship 2019.

Prior to joining Mila, I was a data-scientist at Snips (now acquired by Sonos), working on language understanding for privacy-preserving voice assistants. I also hold a Master in Machine Learning (MVA) from the Ecole Normale Supérieure de Cachan.

Selected publications

  1. UAI
    Discrete Probabilistic Inference as Control in Multi-path Environments
    Uncertainty in Artificial Intelligence, 2024
  2. NeurIPS
    Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network
    Conference on Neural Information Processing Systems, 2023
  3. UAI
    Bayesian Structure Learning with Generative Flow Networks
    Uncertainty in Artificial Intelligence, 2022
  4. ICLR Spotlight
    Continuous-Time Meta-Learning with Forward Mode Differentiation
    International Conference on Learning Representations, 2022
  5. Preprint Best in Show
    Torchmeta: A Meta-Learning library for PyTorch
    arXiv preprint, 2019