| Convergence analysis of machine learning algorithms for the numerical solution of mean field control and games: II—the finite horizon case R Carmona, M Laurière The Annals of Applied Probability 32 (6), 4065-4105, 2022 | 146 | 2022 |
| Fictitious play for mean field games: Continuous time analysis and applications S Perrin, J Pérolat, M Laurière, M Geist, R Elie, O Pietquin Advances in Neural Information Processing Systems 33, 2020 | 133 | 2020 |
| Model-free mean-field reinforcement learning: mean-field MDP and mean-field Q-learning R Carmona, M Laurière, Z Tan The Annals of Applied Probability 33 (6B), 5334-5381, 2023 | 111 | 2023 |
| Mean field games and applications: Numerical aspects Y Achdou, M Laurière Mean Field Games, 249-307, 2020 | 105 | 2020 |
| Dynamic programming for mean-field type control M Laurière, O Pironneau Comptes Rendus Mathematique 352 (9), 707-713, 2014 | 105 | 2014 |
| On the convergence of model free learning in mean field games R Elie, J Perolat, M Laurière, M Geist, O Pietquin Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7143-7150, 2020 | 102 | 2020 |
| Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games I: The Ergodic Case R Carmona, M Laurière SIAM Journal on Numerical Analysis 59 (3), 1455-1485, 2021 | 101 | 2021 |
| COVID-19 pandemic control: balancing detection policy and lockdown intervention under ICU sustainability A Charpentier, R Elie, M Laurière, VC Tran Mathematical Modelling of Natural Phenomena 15, 57, 2020 | 89 | 2020 |
| Optimal incentives to mitigate epidemics: a Stackelberg mean field game approach A Aurell, R Carmona, G Dayanikli, M Lauriere SIAM Journal on Control and Optimization 60 (2), S294-S322, 2022 | 78 | 2022 |
| Linear-Quadratic Mean-Field Reinforcement Learning: Convergence of Policy Gradient Methods R Carmona, M Laurière, Z Tan arXiv preprint arXiv:1910.04295, 2019 | 76 | 2019 |
| Numerical methods for mean field games and mean field type control M Lauriere Mean field games 78 (221-282), 2021 | 72 | 2021 |
| Unified Reinforcement Q-Learning for Mean Field Game and Control Problems A Angiuli, JP Fouque, M Laurière Mathematics of Control, Signals, and Systems (arXiv preprint arXiv:2006.13912), 2020 | 72 | 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 (arXiv preprint arXiv:2103.00623), 2021 | 69 | 2021 |
| 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 (arXiv preprint arXiv:2106.03787), 2021 | 68 | 2021 |
| Convergence of large population games to mean field games with interaction through the controls M Laurière, L Tangpi SIAM Journal on Mathematical Analysis 54 (3), 3535-3574, 2022 | 64 | 2022 |
| On the system of partial differential equations arising in mean field type control Y Achdou, M Lauriere Discrete and Continuous Dynamical Systems 35 (9), 3879-3900, 2015 | 63 | 2015 |
| Stochastic Graphon Games: I. The Static Case R Carmona, D Cooney, C Graves, M Lauriere Mathematics of Operations Research (arXiv preprint arXiv:1911.10664), 2019 | 59 | 2019 |
| Mean field control and mean field game models with several populations A Bensoussan, T Huang, M Laurière arXiv preprint arXiv:1810.00783, 2018 | 57 | 2018 |
| On the implementation of a primal-dual algorithm for second order time-dependent mean field games with local couplings L Briceño-Arias, D Kalise, Z Kobeissi, M Laurière, AM González, FJ Silva ESAIM: Proceedings and Surveys 65, 330-348, 2019 | 55 | 2019 |
| Multipartite Generalization of Quantum Discord C Radhakrishnan, M Laurière, T Byrnes Physical Review Letters 124 (11), 110401, 2020 | 54 | 2020 |
Olivier PietquinCohere | ex Google DeepMind (On leave - Professor at University of Lille)Verified email at univ-lille.fr
