| Gemma 2: Improving open language models at a practical size G Team, M Riviere, S Pathak, PG Sessa, C Hardin, S Bhupatiraju, ... arXiv preprint arXiv:2408.00118, 2024 | 528 | 2024 |
| Fictitious play for mean field games: Continuous time analysis and applications S Perrin, J Pérolat, M Laurière, M Geist, R Elie, O Pietquin NeurIPS 2020, 2020 | 143 | 2020 |
| Scaling up Mean Field Games with Online Mirror Descent J Perolat, S Perrin, R Elie, M Laurière, G Piliouras, M Geist, K Tuyls, ... AAMAS 2022, 2021 | 78 | 2021 |
| Machine learning optimization algorithms & portfolio allocation S Perrin, T Roncalli Machine learning for asset management: New developments and financial …, 2020 | 78 | 2020 |
| Concave Utility Reinforcement Learning: the Mean-field Game viewpoint M Geist, J Pérolat, M Laurière, R Elie, S Perrin, O Bachem, R Munos, ... AAMAS 2022, 2021 | 73 | 2021 |
| Learning in mean field games: A survey M Laurière, S Perrin, J Pérolat, S Girgin, P Muller, R Élie, M Geist, ... arXiv preprint arXiv:2205.12944, 2022 | 63 | 2022 |
| Scalable Deep Reinforcement Learning Algorithms for Mean Field Games M Laurière, S Perrin, S Girgin, P Muller, A Jain, T Cabannes, G Piliouras, ... ICML 2022, 2022 | 62 | 2022 |
| Mean Field Games Flock! The Reinforcement Learning Way S Perrin, M Laurière, J Pérolat, M Geist, R Élie, O Pietquin IJCAI 2021, 2021 | 55 | 2021 |
| Generalization in Mean Field Games by Learning Master Policies S Perrin, M Laurière, J Pérolat, R Élie, M Geist, O Pietquin AAAI 2022, 2021 | 42 | 2021 |
| Solving N-player dynamic routing games with congestion: a mean field approach T Cabannes, M Laurière, J Perolat, R Marinier, S Girgin, S Perrin, ... arXiv preprint arXiv:2110.11943, 2021 | 25 | 2021 |
| Bond: Aligning llms with best-of-n distillation PG Sessa, R Dadashi, L Hussenot, J Ferret, N Vieillard, A Ramé, ... arXiv preprint arXiv:2407.14622, 2024 | 21 | 2024 |
| Learning correlated equilibria in mean-field games P Muller, R Elie, M Rowland, M Lauriere, J Perolat, S Perrin, M Geist, ... arXiv preprint arXiv:2208.10138, 2022 | 15 | 2022 |
| Mean field games flock S Perrin, M Lauriere, J Pérolat, M Geist, R Elie, O Pietquin The reinforcement learning way. In proc. of IJCAI, 2021 | 5 | 2021 |
| Mastering Board Games by External and Internal Planning with Language Models J Schultz, J Adamek, M Jusup, M Lanctot, M Kaisers, S Perrin, D Hennes, ... arXiv preprint arXiv:2412.12119, 2024 | 3 | 2024 |
| Diversity-rewarded CFG distillation G Cideron, A Agostinelli, J Ferret, S Girgin, R Elie, O Bachem, S Perrin, ... arXiv preprint arXiv:2410.06084, 2024 | 3 | 2024 |
| Approximating the core via iterative coalition sampling I Gemp, M Lanctot, L Marris, Y Mao, E Duéñez-Guzmán, S Perrin, ... arXiv preprint arXiv:2402.03928, 2024 | 2 | 2024 |
| Scaling up Multi-agent Reinforcement Learning with Mean Field Games and Vice-versa S Perrin Université de Lille, 2022 | 1 | 2022 |
| On Teacher Hacking in Language Model Distillation D Tiapkin, D Calandriello, J Ferret, S Perrin, N Vieillard, A Ramé, ... arXiv preprint arXiv:2502.02671, 2025 | | 2025 |
| Mise à l'échelle de l'apprentissage par renforcement multi-agent grâce aux jeux à champ moyen et vice-versa S Perrin | | 2022 |
| Learning algorithms for Mean Field Games R Elie, M Geist, M Laurière, J Pérolat, S Perrin, O Pietquin, G Pilliouras, ... PGMO DAYS 2021, 42, 2021 | | 2021 |
Romuald ElieDeepmind & Université Gustave EiffelVahvistettu sähköpostiosoite verkkotunnuksessa u-pem.fr