Tristan Deleu
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A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
Y Bengio, T Deleu, N Rahaman, R Ke, S Lachapelle, O Bilaniuk, A Goyal, ...
International Conference on Learning Representations (ICLR 2020), 2019
Gradient-Based Neural DAG Learning
S Lachapelle, P Brouillard, T Deleu, S Lacoste-Julien
International Conference on Learning Representations (ICLR 2020), 2019
Gflownet foundations
Y Bengio, S Lahlou, T Deleu, EJ Hu, M Tiwari, E Bengio
The Journal of Machine Learning Research 24 (1), 10006-10060, 2023
Bayesian structure learning with generative flow networks
T Deleu, A Góis, C Emezue, M Rankawat, S Lacoste-Julien, S Bauer, ...
Uncertainty in Artificial Intelligence, 518-528, 2022
Torchmeta: A meta-learning library for pytorch
T Deleu, T Würfl, M Samiei, JP Cohen, Y Bengio
arXiv preprint arXiv:1909.06576, 2019
GFlowNets and variational inference
N Malkin, S Lahlou, T Deleu, X Ji, E Hu, K Everett, D Zhang, Y Bengio
arXiv preprint arXiv:2210.00580, 2022
A theory of continuous generative flow networks
S Lahlou, T Deleu, P Lemos, D Zhang, A Volokhova, A Hernández-Garcıa, ...
International Conference on Machine Learning, 18269-18300, 2023
Covi white paper
H Alsdurf, E Belliveau, Y Bengio, T Deleu, P Gupta, D Ippolito, R Janda, ...
arXiv preprint arXiv:2005.08502, 2020
Gflownets for ai-driven scientific discovery
M Jain, T Deleu, J Hartford, CH Liu, A Hernandez-Garcia, Y Bengio
Digital Discovery 2 (3), 557-577, 2023
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network
T Deleu, M Nishikawa-Toomey, J Subramanian, N Malkin, L Charlin, ...
Neural Information Processing Systems 2023, 2023
The effects of negative adaptation in model-agnostic meta-learning
T Deleu, Y Bengio
arXiv preprint arXiv:1812.02159, 2018
Synergies between disentanglement and sparsity: Generalization and identifiability in multi-task learning
S Lachapelle, T Deleu, D Mahajan, I Mitliagkas, Y Bengio, ...
International Conference on Machine Learning, 18171-18206, 2023
Bayesian learning of causal structure and mechanisms with gflownets and variational bayes
M Nishikawa-Toomey, T Deleu, J Subramanian, Y Bengio, L Charlin
arXiv preprint arXiv:2211.02763, 2022
Predicting infectiousness for proactive contact tracing
Y Bengio, P Gupta, T Maharaj, N Rahaman, M Weiss, T Deleu, E Muller, ...
arXiv preprint arXiv:2010.12536, 2020
Continuous-Time Meta-Learning with Forward Mode Differentiation
T Deleu, D Kanaa, L Feng, G Kerg, Y Bengio, G Lajoie, PL Bacon
International Conference on Learning Representations (ICLR 2022), 2022
Curriculum in gradient-based meta-reinforcement learning
B Mehta, T Deleu, SC Raparthy, CJ Pal, L Paull
arXiv preprint arXiv:2002.07956, 2020
Structured sparsity inducing adaptive optimizers for deep learning
T Deleu, Y Bengio
arXiv preprint arXiv:2102.03869, 2021
COVI-AgentSim: an agent-based model for evaluating methods of digital contact tracing
P Gupta, T Maharaj, M Weiss, N Rahaman, H Alsdurf, A Sharma, ...
arXiv preprint arXiv:2010.16004, 2020
Learning operations on a stack with Neural Turing Machines
T Deleu, J Dureau
arXiv preprint arXiv:1612.00827, 2016
Model-Agnostic Meta-Learning for Reinforcement Learning in PyTorch, 2018
T Deleu
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