Tristan Deleu

PhD student, University of Montreal

Joined

October 2016

Names

Tristan Deleu (Preferred)

Emails

****@gmail.com (Confirmed)

****@mila.quebec (Confirmed)

****@umontreal.ca

Personal Links

Homepage

Google Scholar

DBLP

Career & Education History

PhD student

University of Montreal (umontreal.ca)

2018 – Present

MS student

University of Montreal (umontreal.ca)

2017 – 2018

Advisors, Relations & Conflicts

PhD Advisor

Yoshua Bengio

2017 – Present

Expertise

Bayesian Structure Learning

Causal Discovery

Generative Flow Networks

2021 – Present

Meta-Learning

Few-shot learning

Memory-Augmented Neural Networks

2016 – Present

Publications

Accelerating Ammonia Decomposition Catalyst Discovery with AI
Samuel P. Gleason, Mathilde L. D. Franckel, Martin Siron, Alan Barrios, Richard Tran, Joseph Musielewicz, Piyusa Priyadarsan Pattanaik, Anvesh Nathani, Tristan Deleu, Etienne du Fayet, Jean-Gabriel Argaud, Sagar Pal, Hannah Bull, Cory Hargus, Svetlana Heyte, Victor Schmidt, Egon Heuson, Sébastien Paul, Alexandre Duval
- AI4X-AC 2026 Oral
- Readers: Everyone
Gymnasium: A Standard Interface for Reinforcement Learning Environments
Mark Towers, Ariel Kwiatkowski, John U. Balis, Gianluca De Cola, Tristan Deleu, Manuel Goulão, Kallinteris Andreas, Markus Krimmel, Arjun KG, Rodrigo De Lazcano Perez-Vicente, J K Terry, Andrea Pierré, Sander V Schulhoff, Jun Jet Tai, Hannah Tan, Omar G. Younis
- NeurIPS 2025 Datasets and Benchmarks Track spotlight
- Readers: Everyone
Gymnasium: A Standard Interface for Reinforcement Learning Environments
Ariel Kwiatkowski, Mark Towers, J K Terry, John U. Balis, Gianluca De Cola, Tristan Deleu, Manuel Goulão, Kallinteris Andreas, Markus Krimmel, Arjun KG, Rodrigo De Lazcano Perez-Vicente, Andrea Pierré, Sander V Schulhoff, Jun Jet Tai, Hannah Tan, Omar G. Younis
- Submitted to ICLR 2025
- Readers: Everyone
Discrete Probabilistic Inference as Control in Multi-path Environments
Tristan Deleu, Padideh Nouri, Nikolay Malkin, Doina Precup, Yoshua Bengio
- UAI 2024 poster
- Readers: Everyone
Learning Latent Structural Causal Models
Jithendaraa Subramanian, Yashas Annadani, Tristan Deleu, Ivaxi Sheth, Nan Rosemary Ke, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou
- Submitted to ICLR 2024
- Readers: Everyone
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation
Chris Chinenye Emezue, Alexandre Drouin, Tristan Deleu, Stefan Bauer, Yoshua Bengio
- 1st SPIGM @ ICML Poster
- Readers: Everyone
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network
Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio
- 1st SPIGM @ ICML Oral
- Readers: Everyone
BatchGFN: Generative Flow Networks for Batch Active Learning
Shreshth A Malik, Salem Lahlou, Andrew Jesson, Moksh Jain, Nikolay Malkin, Tristan Deleu, Yoshua Bengio, Yarin Gal
- 1st SPIGM @ ICML Poster
- Readers: Everyone
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network
Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio
- NeurIPS 2023 poster
- Readers: Everyone
Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning
Sebastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand
- ICML 2023 Poster
- Readers: Everyone

View all 42 publications

Co-Authors

View all 114 co-authors