Salem Lahlou

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 20

Top Topics

Top Venues

J. Mach. Learn. Res.

Publications

Anas Krichel, Nikolay Malkin, Salem Lahlou, Yoshua Bengio
On Generalization for Generative Flow Networks. CoRR (2024)
Salem Lahlou, Abdalgader Abubaker, Hakim Hacid
PORT: Preference Optimization on Reasoning Traces. CoRR (2024)
Réda Alami, Abdalgader Abubaker, Mastane Achab, Mohamed El Amine Seddik, Salem Lahlou
Investigating Regularization of Self-Play Language Models. CoRR (2024)
Salem Lahlou, Joseph D. Viviano, Victor Schmidt
torchgfn: A PyTorch GFlowNet library. CoRR (2023)
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 (2023)
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)
Dianbo Liu, Moksh Jain, Bonaventure F. P. Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Chinenye Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio
GFlowOut: Dropout with Generative Flow Networks. ICML (2023)
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 (2023)
Salem Lahlou, Moksh Jain, Hadi Nekoei, Victor Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio
DEUP: Direct Epistemic Uncertainty Prediction. Trans. Mach. Learn. Res. 2023 (2023)
Maxime Chevalier-Boisvert, Bolun Dai, Mark Towers, Rodrigo de Lazcano, Lucas Willems, Salem Lahlou, Suman Pal, Pablo Samuel Castro, Jordan Terry
Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks. CoRR (2023)
Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio
GFlowNets and variational inference. ICLR (2023)
Maxime Chevalier-Boisvert, Bolun Dai, Mark Towers, Rodrigo Perez-Vicente, Lucas Willems, Salem Lahlou, Suman Pal, Pablo Samuel Castro, Jordan Terry
Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks. NeurIPS (2023)
Yoshua Bengio, Salem Lahlou, Tristan Deleu, Edward J. Hu, Mo Tiwari, Emmanuel Bengio
GFlowNet Foundations. J. Mach. Learn. Res. 24 (2023)
Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio
GFlowNets and variational inference. CoRR (2022)
Dianbo Liu, Moksh Jain, Bonaventure Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio
GFlowOut: Dropout with Generative Flow Networks. CoRR (2022)
Moksh Jain, Salem Lahlou, Hadi Nekoei, Victor Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio
DEUP: Direct Epistemic Uncertainty Prediction. CoRR (2021)
Yoshua Bengio, Tristan Deleu, Edward J. Hu, Salem Lahlou, Mo Tiwari, Emmanuel Bengio
GFlowNet Foundations. CoRR (2021)
Lucas Willems, Salem Lahlou, Yoshua Bengio
Mastering Rate based Curriculum Learning. CoRR (2020)
Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, Lucas Willems, Chitwan Saharia, Thien Huu Nguyen, Yoshua Bengio
BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning. ICLR (Poster) (2019)
Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, Lucas Willems, Chitwan Saharia, Thien Huu Nguyen, Yoshua Bengio
BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop. CoRR (2018)