| Temperature decreases spread parameters of the new Covid-19 case dynamics J Demongeot, Y Flet-Berliac, H Seligmann Biology 9 (5), 94, 2020 | 157 | 2020 |
| Adversarially Guided Actor-Critic Y Flet-Berliac, J Ferret, O Pietquin, P Preux, M Geist ICLR 2021, 2021 | 79 | 2021 |
| The Promise of Hierarchical Reinforcement Learning Y Flet-Berliac The Gradient, 2019 | 32 | 2019 |
| Learning Value Functions in Deep Policy Gradients using Residual Variance Y Flet-Berliac, R Ouhamma, OA Maillard, P Preux ICLR 2021, 2021 | 21 | 2021 |
| rlberry - A Reinforcement Learning Library for Research and Education OD Domingues, Y Flet-Berliac, E Leurent, P Ménard, X Shang, M Valko GitHub repository, 2021 | 18 | 2021 |
| Hearables in hearing care: Discovering usage patterns through IoT devices B Johansen, Y Flet-Berliac, M Korzepa, P Sandholm, N Pontoppidan, ... International Conference on Universal Access in Human-Computer Interaction …, 2017 | 18 | 2017 |
| Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data A Nie, Y Flet-Berliac, D Richmond, W Steenbergen, E Brunskill NeurIPS 2022, 2022 | 14 | 2022 |
| SAAC: Safe Reinforcement Learning as an Adversarial Game of Actor-Critics Y Flet-Berliac, D Basu RLDM 2022, 2022 | 12 | 2022 |
| MERL: Multi-Head Reinforcement Learning Y Flet-Berliac, P Preux NeurIPS 2019 Deep Reinforcement Learning Workshop, 2019 | 12 | 2019 |
| Learning Preferences and Soundscapes for Augmented Hearing MJ Korzepa, B Johansen, MK Petersen, J Larsen, JE Larsen, ... IUI Workshops, 2018 | 12 | 2018 |
| Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets A Badrinath, Y Flet-Berliac, A Nie, E Brunskill NeurIPS 2023, 2023 | 9 | 2023 |
| Only Relevant Information Matters: Filtering Out Noisy Samples to Boost RL Y Flet-Berliac, P Preux IJCAI 2020, 2020 | 9* | 2020 |
| PASTA: Pretrained Action-State Transformer Agents R Boige, Y Flet-Berliac, A Flajolet, G Richard, T Pierrot NeurIPS 2023 Foundation Models for Decision Making Workshop, 2023 | 4 | 2023 |
| Offline Policy Optimization with Eligible Actions Y Liu, Y Flet-Berliac, E Brunskill UAI 2022, 2022 | 4 | 2022 |
| Model-based Offline Reinforcement Learning with Local Misspecification K Dong, Y Flet-Berliac, A Nie, E Brunskill AAAI 2023, 2023 | 1 | 2023 |
| Sample-Efficient Deep Reinforcement Learning for Control, Exploration and Safety Y Flet-Berliac | 1 | 2021 |
| High-Dimensional Control Using Generalized Auxiliary Tasks Y Flet-Berliac, P Preux Research Report hal-02295705, 2019 | 1 | 2019 |
| Averaging log-likelihoods in direct alignment N Grinsztajn, Y Flet-Berliac, MG Azar, F Strub, B Wu, E Choi, C Cremer, ... arXiv preprint arXiv:2406.19188, 2024 | | 2024 |
| Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion Y Flet-Berliac, N Grinsztajn, F Strub, E Choi, C Cremer, A Ahmadian, ... arXiv preprint arXiv:2406.19185, 2024 | | 2024 |
| OPERA: Automatic Offline Policy Evaluation with Re-weighted Aggregates of Multiple Estimators A Nie, Y Chandak, CJ Yuan, A Badrinath, Y Flet-Berliac, E Brunskil arXiv preprint arXiv:2405.17708, 2024 | | 2024 |
Philippe PreuxProfessor of computer science, Université de Lille, LIFL, SequeL, INRIA在 univ-lille.fr 的电子邮件经过验证
