| Babyai: A platform to study the sample efficiency of grounded language learning M Chevalier-Boisvert, D Bahdanau, S Lahlou, L Willems, C Saharia, ... International Conference on Learning Representations, 2019, 2018 | 432* | 2018 |
| Gflownet foundations Y Bengio, S Lahlou, T Deleu, EJ Hu, M Tiwari, E Bengio Journal of Machine Learning Research 24 (210), 1-55, 2023 | 238 | 2023 |
| Minigrid & miniworld: Modular & customizable reinforcement learning environments for goal-oriented tasks M Chevalier-Boisvert, B Dai, M Towers, R Perez-Vicente, L Willems, ... Advances in Neural Information Processing Systems 36, 73383-73394, 2023 | 206 | 2023 |
| 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 | 85 | 2023 |
| GFlowNets and variational inference N Malkin, S Lahlou, T Deleu, X Ji, E Hu, K Everett, D Zhang, Y Bengio International Conference on Learning Representations, 2023, 2022 | 83 | 2022 |
| DEUP: Direct Epistemic Uncertainty Prediction S Lahlou, M Jain, H Nekoei, V Butoi, P Bertin, J Rector-Brooks, ... Transactions On Machine Learning Research, 2022 | 67 | 2022 |
| Deup: Direct epistemic uncertainty prediction M Jain, S Lahlou, H Nekoei, VI Butoi, P Bertin, J Rector-Brooks, ... | 52 | 2021 |
| Gflowout: Dropout with generative flow networks D Liu, M Jain, BFP Dossou, Q Shen, S Lahlou, A Goyal, N Malkin, ... International Conference on Machine Learning, 21715-21729, 2023 | 21 | 2023 |
| A Nash equilibrium formulation of a tradable credits scheme for incentivizing transport choices: From next-generation public transport mode choice to HOT lanes S Lahlou, L Wynter Transportation Research Part B: Methodological 101, 185-212, 2017 | 17 | 2017 |
| Mastering rate based curriculum learning L Willems, S Lahlou, Y Bengio arXiv preprint arXiv:2008.06456, 2020 | 7 | 2020 |
| torchgfn: A pytorch gflownet library S Lahlou, JD Viviano, V Schmidt, Y Bengio arXiv preprint arXiv:2305.14594, 2023 | 4 | 2023 |
| Batchgfn: Generative flow networks for batch active learning SA Malik, S Lahlou, A Jesson, M Jain, N Malkin, T Deleu, Y Bengio, Y Gal ICML2023 SPIGM, 2023 | 3 | 2023 |
| On Generalization for Generative Flow Networks A Krichel, N Malkin, S Lahlou, Y Bengio arXiv preprint arXiv:2407.03105, 2024 | 1 | 2024 |
| Investigating Regularization of Self-Play Language Models R Alami, A Abubaker, M Achab, MEA Seddik, S Lahlou arXiv preprint arXiv:2404.04291, 2024 | 1 | 2024 |
| Advances in uncertainty modelling: from epistemic uncertainty estimation to generalized generative flow networks S Lahlou | 1 | 2024 |
| On the Privacy Risks of Spiking Neural Networks: A Membership Inference Analysis J Guan, A Sharma, C Tian, S Lahlou arXiv preprint arXiv:2502.13191, 2025 | | 2025 |
| PORT: Preference Optimization on Reasoning Traces S Lahlou, A Abubaker, H Hacid arXiv preprint arXiv:2406.16061, 2024 | | 2024 |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARยืนยันอีเมลแล้วที่ umontreal.ca