Tristan Deleu

Mila - Quebec Artificial Intelligence Institute · Université de Montréal

I am a fifth year Ph.D. candidate at Mila & Université de Montréal, under the supervision of Yoshua Bengio. My research interests include Probabilistic Modeling, Structure Learning, Meta-Learning, Few-shot 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
    Bayesian Structure Learning with Generative Flow Networks
    Uncertainty in Artificial Intelligence 2022
  2. ICLR Spotlight
    Continuous-Time Meta-Learning with Forward Mode Differentiation
    International Conference on Learning Representations 2022
  3. ICLR Spotlight
    Predicting Infectiousness for Proactive Contact Tracing
    Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Muller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, and others
    International Conference on Learning Representations 2021
  4. ICLR
    A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
    International Conference on Learning Representations 2020
  5. Preprint Best in Show
    Torchmeta: A Meta-Learning library for PyTorch
    arXiv preprint 2019