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Tristan Deleu
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2020 – today
- 2024
- [i29]Tristan Deleu, Padideh Nouri, Nikolay Malkin, Doina Precup, Yoshua Bengio:
Discrete Probabilistic Inference as Control in Multi-path Environments. CoRR abs/2402.10309 (2024) - [i28]Mark Towers, Ariel Kwiatkowski, Jordan K. Terry, John U. Balis, Gianluca De Cola, Tristan Deleu, Manuel Goulão, Andreas Kallinteris, Markus Krimmel, Arjun KG, Rodrigo Perez-Vicente, Andrea Pierré, Sander Schulhoff, Jun Jet Tai, Hannah Tan, Omar G. Younis:
Gymnasium: A Standard Interface for Reinforcement Learning Environments. CoRR abs/2407.17032 (2024) - 2023
- [j1]Yoshua Bengio, Salem Lahlou, Tristan Deleu, Edward J. Hu, Mo Tiwari, Emmanuel Bengio:
GFlowNet Foundations. J. Mach. Learn. Res. 24: 210:1-210:55 (2023) - [c10]Ramnath Kumar, Tristan Deleu, Yoshua Bengio:
The Effect of Diversity in Meta-Learning. AAAI 2023: 8396-8404 - [c9]Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio:
GFlowNets and variational inference. ICLR 2023 - [c8]Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand:
Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning. ICML 2023: 18171-18206 - [c7]Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin:
A theory of continuous generative flow networks. ICML 2023: 18269-18300 - [c6]Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio:
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network. NeurIPS 2023 - [i27]Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin:
A theory of continuous generative flow networks. CoRR abs/2301.12594 (2023) - [i26]Moksh Jain, Tristan Deleu, Jason S. Hartford, Cheng-Hao Liu, Alex Hernández-García, Yoshua Bengio:
GFlowNets for AI-Driven Scientific Discovery. CoRR abs/2302.00615 (2023) - [i25]Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio:
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network. CoRR abs/2305.19366 (2023) - [i24]Shreshth A. Malik, Salem Lahlou, Andrew Jesson, Moksh Jain, Nikolay Malkin, Tristan Deleu, Yoshua Bengio, Yarin Gal:
BatchGFN: Generative Flow Networks for Batch Active Learning. CoRR abs/2306.15058 (2023) - [i23]Tristan Deleu, Yoshua Bengio:
Generative Flow Networks: a Markov Chain Perspective. CoRR abs/2307.01422 (2023) - [i22]Chris Chinenye Emezue, Alexandre Drouin, Tristan Deleu, Stefan Bauer, Yoshua Bengio:
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation. CoRR abs/2307.04988 (2023) - 2022
- [c5]Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon:
Continuous-Time Meta-Learning with Forward Mode Differentiation. ICLR 2022 - [c4]Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio:
Bayesian structure learning with generative flow networks. UAI 2022: 518-528 - [i21]Ramnath Kumar, Tristan Deleu, Yoshua Bengio:
The Effect of Diversity in Meta-Learning. CoRR abs/2201.11775 (2022) - [i20]Ramnath Kumar, Tristan Deleu, Yoshua Bengio:
Rethinking Learning Dynamics in RL using Adversarial Networks. CoRR abs/2201.11783 (2022) - [i19]Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio:
Bayesian Structure Learning with Generative Flow Networks. CoRR abs/2202.13903 (2022) - [i18]Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon:
Continuous-Time Meta-Learning with Forward Mode Differentiation. CoRR abs/2203.01443 (2022) - [i17]Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio:
GFlowNets and variational inference. CoRR abs/2210.00580 (2022) - [i16]Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Nan Rosemary Ke, Tristan Deleu, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou:
Learning Latent Structural Causal Models. CoRR abs/2210.13583 (2022) - [i15]Mizu Nishikawa-Toomey, Tristan Deleu, Jithendaraa Subramanian, Yoshua Bengio, Laurent Charlin:
Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes. CoRR abs/2211.02763 (2022) - [i14]Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand:
Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective. CoRR abs/2211.14666 (2022) - 2021
- [c3]Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Benjamin Müller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David L. Buckeridge, Gaétan Marceau-Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Christopher J. Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams:
Predicting Infectiousness for Proactive Contact Tracing. ICLR 2021 - [i13]Tristan Deleu, Yoshua Bengio:
Structured Sparsity Inducing Adaptive Optimizers for Deep Learning. CoRR abs/2102.03869 (2021) - [i12]Yoshua Bengio, Tristan Deleu, Edward J. Hu, Salem Lahlou, Mo Tiwari, Emmanuel Bengio:
GFlowNet Foundations. CoRR abs/2111.09266 (2021) - 2020
- [c2]Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal:
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. ICLR 2020 - [c1]Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien:
Gradient-Based Neural DAG Learning. ICLR 2020 - [i11]Bhairav Mehta, Tristan Deleu, Sharath Chandra Raparthy, Christopher J. Pal, Liam Paull:
Curriculum in Gradient-Based Meta-Reinforcement Learning. CoRR abs/2002.07956 (2020) - [i10]Hannah Alsdurf, Yoshua Bengio, Tristan Deleu, Prateek Gupta, Daphne Ippolito, Richard Janda, Max Jarvie, Tyler Kolody, Sekoul Krastev, Tegan Maharaj, Robert Obryk, Dan Pilat, Valerie Pisano, Benjamin Prud'homme, Meng Qu, Nasim Rahaman, Irina Rish, Jean-Franois Rousseau, Abhinav Sharma, Brooke Struck, Jian Tang, Martin Weiss, Yun William Yu:
COVI White Paper. CoRR abs/2005.08502 (2020) - [i9]Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif B. Müller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David L. Buckeridge, Gaétan Marceau Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Chris Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams:
Predicting Infectiousness for Proactive Contact Tracing. CoRR abs/2010.12536 (2020) - [i8]Prateek Gupta, Tegan Maharaj, Martin Weiss, Nasim Rahaman, Hannah Alsdurf, Abhinav Sharma, Nanor Minoyan, Soren Harnois-Leblanc, Victor Schmidt, Pierre-Luc St-Charles, Tristan Deleu, Andrew Williams, Akshay Patel, Meng Qu, Olexa Bilaniuk, Gaétan Marceau Caron, Pierre Luc Carrier, Satya Ortiz-Gagné, Marc-Andre Rousseau, David L. Buckeridge, Joumana Ghosn, Yang Zhang, Bernhard Schölkopf, Jian Tang, Irina Rish, Christopher Joseph Pal, Joanna Merckx, Eilif B. Müller, Yoshua Bengio:
COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing. CoRR abs/2010.16004 (2020)
2010 – 2019
- 2019
- [i7]Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal:
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. CoRR abs/1901.10912 (2019) - [i6]Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien:
Gradient-Based Neural DAG Learning. CoRR abs/1906.02226 (2019) - [i5]Shagun Sodhani, Anirudh Goyal, Tristan Deleu, Yoshua Bengio, Sergey Levine, Jian Tang:
Learning Powerful Policies by Using Consistent Dynamics Model. CoRR abs/1906.04355 (2019) - [i4]Tristan Deleu, Tobias Würfl, Mandana Samiei, Joseph Paul Cohen, Yoshua Bengio:
Torchmeta: A Meta-Learning library for PyTorch. CoRR abs/1909.06576 (2019) - [i3]Mandana Samiei, Tobias Würfl, Tristan Deleu, Martin Weiss, Francis Dutil, Thomas Fevens, Geneviève Boucher, Sébastien Lemieux, Joseph Paul Cohen:
The TCGA Meta-Dataset Clinical Benchmark. CoRR abs/1910.08636 (2019) - 2018
- [i2]Tristan Deleu, Yoshua Bengio:
The effects of negative adaptation in Model-Agnostic Meta-Learning. CoRR abs/1812.02159 (2018) - 2016
- [i1]Tristan Deleu, Joseph Dureau:
Learning Operations on a Stack with Neural Turing Machines. CoRR abs/1612.00827 (2016)
Coauthor Index
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last updated on 2024-10-07 22:12 CEST by the dblp team
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