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Tristan Deleu
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GFlowNets for AI-Driven Scientific Discovery


Feb 01, 2023
Moksh Jain, Tristan Deleu, Jason Hartford, Cheng-Hao Liu, Alex Hernandez-Garcia, Yoshua Bengio

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* 26 pages, 5 figures 
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A theory of continuous generative flow networks


Jan 30, 2023
Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin

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* 31 pages; code: https://github.com/saleml/continuous-gfn 
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Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective


Nov 26, 2022
SĂ©bastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand

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* 36 pages 
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Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes


Nov 04, 2022
Mizu Nishikawa-Toomey, Tristan Deleu, Jithendaraa Subramanian, Yoshua Bengio, Laurent Charlin

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Learning Latent Structural Causal Models


Oct 24, 2022
Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Nan Rosemary Ke, Tristan Deleu, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou

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* 21 pages, 19 figures 
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GFlowNets and variational inference


Oct 02, 2022
Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio

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Continuous-Time Meta-Learning with Forward Mode Differentiation


Mar 02, 2022
Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon

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Bayesian Structure Learning with Generative Flow Networks


Feb 28, 2022
Tristan Deleu, AntĂłnio GĂłis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio

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Rethinking Learning Dynamics in RL using Adversarial Networks


Jan 27, 2022
Ramnath Kumar, Tristan Deleu, Yoshua Bengio

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The Effect of Diversity in Meta-Learning


Jan 27, 2022
Ramnath Kumar, Tristan Deleu, Yoshua Bengio

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