Mathieu Laurière
Princeton University
H-index: 27
North America-United States
Top articles of Mathieu Laurière
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
Deep Backward and Galerkin Methods for the Finite State Master Equation | arXiv preprint arXiv:2403.04975 | Asaf Cohen Mathieu Laurière Ethan Zell | 2024/3/8 |
Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning | arXiv preprint arXiv:2403.03552 | Zida Wu Mathieu Laurière Samuel Jia Cong Chua Matthieu Geist Olivier Pietquin | 2024/3/6 |
On Imitation in Mean-field Games | Advances in Neural Information Processing Systems | Giorgia Ramponi Pavel Kolev Olivier Pietquin Niao He Mathieu Laurière | 2024/2/13 |
A Deep Learning Method for Optimal Investment Under Relative Performance Criteria Among Heterogeneous Agents | arXiv preprint arXiv:2402.07365 | Mathieu Laurière Ludovic Tangpi Xuchen Zhou | 2024/2/12 |
Independent RL for Cooperative-Competitive Agents: A Mean-Field Perspective | arXiv preprint arXiv:2403.11345 | Muhammad Aneeq Uz Zaman Alec Koppel Mathieu Laurière Tamer Başar | 2024/3/17 |
Actor-Critic learning for mean-field control in continuous time | arXiv preprint arXiv:2303.06993 | Noufel Frikha Maximilien Germain Mathieu Laurière Huyên Pham Xuanye Song | 2023/3/13 |
Machine learning architectures for price formation models | Applied Mathematics & Optimization | Diogo Gomes Julian Gutierrez Mathieu Laurière | 2023/8 |
From Nash Equilibrium to Social Optimum and vice versa: a Mean Field Perspective | arXiv preprint arXiv:2312.10526 | Rene Carmona Gokce Dayanikli Francois Delarue Mathieu Lauriere | 2023/12/16 |
Deep Learning for Population-Dependent Controls in Mean Field Control Problems | arXiv preprint arXiv:2306.04788 | Gokce Dayanikli Mathieu Lauriere Jiacheng Zhang | 2023/6/7 |
Deep Learning for Mean Field Optimal Transport | arXiv preprint arXiv:2302.14739 | Sebastian Baudelet Brieuc Frénais Mathieu Laurière Amal Machtalay Yuchen Zhu | 2023/2/28 |
Convergence of Multi-Scale Reinforcement Q-Learning Algorithms for Mean Field Game and Control Problems | arXiv preprint arXiv:2312.06659 | Andrea Angiuli Jean-Pierre Fouque Mathieu Laurière Mengrui Zhang | 2023/12/11 |
The communication complexity of functions with large outputs | Lila Fontes Sophie Laplante Mathieu Lauriere Alexandre Nolin | 2023/5/25 | |
A Machine Learning Method for Stackelberg Mean Field Games | arXiv preprint arXiv:2302.10440 | Gokce Dayanikli Mathieu Lauriere | 2023/2/21 |
Non-standard Stochastic Control with Nonlinear Feynman-Kac Costs | arXiv preprint arXiv:2312.00908 | Rene Carmona Mathieu Lauriere Pierre-Louis Lions | 2023/12/1 |
Policy iteration method for time-dependent Mean Field Games systems with non-separable Hamiltonians | Applied Mathematics & Optimization | Mathieu Laurière Jiahao Song Qing Tang | 2023/4 |
Model-free mean-field reinforcement learning: mean-field MDP and mean-field Q-learning | The Annals of Applied Probability | René Carmona Mathieu Laurière Zongjun Tan | 2023/12 |
Recent developments in machine learning methods for stochastic control and games | Ruimeng Hu Mathieu Laurière | 2023/3/17 | |
Multi-population Mean Field Games with Multiple Major Players: Application to Carbon Emission Regulations | arXiv preprint arXiv:2309.16477 | Gokce Dayanikli Mathieu Lauriere | 2023/9/28 |
Learning Discrete-Time Major-Minor Mean Field Games | Proceedings of the AAAI Conference on Artificial Intelligence | Kai Cui Gökçe Dayanıklı Mathieu Laurière Matthieu Geist Olivier Pietquin | 2024/3/24 |
Backward propagation of chaos | Electronic Journal of Probability | Mathieu Laurière Ludovic Tangpi | 2022 |
Co-Authors
