Mathieu Laurière

114 papers A* 9A 8B 1C 2Journal 83Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Bench-MFG: A Benchmark Suite for Learning in Stationary Mean Field Games. CoRR Lorenzo Magnino, Jiacheng Shen, Matthieu Geist, Olivier Pietquin, Mathieu Laurière
2026	J	`jnl`	Clustering in Deep Stochastic Transformers. CoRR Lev Fedorov, Michael E. Sander, Romuald Elie, Pierre Marion, Mathieu Laurière
2026	J	`jnl`	Controlling Exploration-Exploitation in GFlowNets via Markov Chain Perspectives. CoRR Lin Chen, Samuel Drapeau, Fanghao Shao, Xuekai Zhu, Bo Xue, Yunchong Song, Mathieu Laurière, Zhouhan Lin
2025	—	`conf`	A Game-Theoretic Framework for Network Formation in Large Populations. CDC Gökçe Dayanikli, Mathieu Laurière
2025	J	`jnl`	A Game-Theoretic Framework for Network Formation in Large Populations. CoRR Gökçe Dayanikli, Mathieu Laurière
2025	J	`jnl`	A Machine Learning Method for Stackelberg Mean Field Games. Math. Oper. Res. Gökçe Dayanikli, Mathieu Laurière
2025	C	`conf`	A Stackelberg Mean Field Game for Green Regulator with a Large Number of Prosumers. ACC Maxim Bichuch, Gökçe Dayanikli, Mathieu Laurière
2025	J	`jnl`	A deep learning method for optimal investment under relative performance criteria among heterogeneous agents. Eur. J. Oper. Res. Mathieu Laurière, Ludovic Tangpi, Xuchen Zhou
2025	J	`jnl`	Actor-Critic learning for mean-field control in continuous time. J. Mach. Learn. Res. Noufel Frikha, Maximilien Germain, Mathieu Laurière, Huyên Pham, Xuanye Song
2025	J	`jnl`	An Overview of Some Extensions of Mean Field Games beyond Perfect Homogeneity and Anonymity. CoRR Mathieu Laurière
2025	J	`jnl`	An overview of some extensions of mean field games beyond perfect homogeneity and anonymity. Sci. China Inf. Sci. Mathieu Laurière
2025	J	`jnl`	Convergence of Actor-Critic Learning for Mean Field Games and Mean Field Control in Continuous Spaces. CoRR Jean-Pierre Fouque, Mathieu Laurière, Mengrui Zhang
2025	J	`jnl`	Deep Learning for the Multiple Optimal Stopping Problem. CoRR Mathieu Laurière, Mehdi Talbi
2025	A*	`conf`	Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean Field Games. ICML Antonio Ocello, Daniil Tiapkin, Lorenzo Mancini, Mathieu Laurière, Eric Moulines
2025	J	`jnl`	Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean-Field Games. CoRR Antonio Ocello, Daniil Tiapkin, Lorenzo Mancini, Mathieu Laurière, Eric Moulines
2025	J	`jnl`	Learning Equilibria in Cournot Mean Field Games of Controls. SIAM J. Control. Optim. Fabio Camilli, Mathieu Laurière, Qing Tang
2025	A*	`conf`	Learning to Stop: Deep Learning for Mean Field Optimal Stopping. ICML Lorenzo Magnino, Yuchen Zhu, Mathieu Laurière
2025	—	`conf`	Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning. CDC Zida Wu, Mathieu Laurière, Matthieu Geist, Olivier Pietquin, Ankur Mehta
2025	J	`jnl`	Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning. CoRR Zida Wu, Mathieu Laurière, Matthieu Geist, Olivier Pietquin, Ankur Mehta
2025	J	`jnl`	Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamics. CoRR Lorenzo Magnino, Kai Shao, Zida Wu, Jiacheng Shen, Mathieu Laurière
2024	J	`jnl`	A Deep Learning Method for Optimal Investment Under Relative Performance Criteria Among Heterogeneous Agents. CoRR Mathieu Laurière, Ludovic Tangpi, Xuchen Zhou
2024	J	`jnl`	A Game-Theoretic Framework for Generic Second-Order Traffic Flow Models Using Mean Field Games and Adversarial Inverse Reinforcement Learning. Transp. Sci. Zhaobin Mo, Xu Chen, Xuan Di, Elisa Iacomini, Chiara Segala, Michael Herty, Mathieu Laurière
2024	J	`jnl`	A Simulation-Free Deep Learning Approach to Stochastic Optimal Control. CoRR Mengjian Hua, Mathieu Laurière, Eric Vanden-Eijnden
2024	J	`jnl`	Analysis of Multiscale Reinforcement Q-Learning Algorithms for Mean Field Control Games. CoRR Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière, Mengrui Zhang
2024	J	`jnl`	Connecting GANs, Mean-Field Games, and Optimal Transport. SIAM J. Appl. Math. Haoyang Cao, Xin Guo, Mathieu Laurière
2024	J	`jnl`	Deep Backward and Galerkin Methods for the Finite State Master Equation. J. Mach. Learn. Res. Asaf Cohen, Mathieu Laurière, Ethan C. Zell
2024	J	`jnl`	Deep Learning Algorithms for Mean Field Optimal Stopping in Finite Space and Discrete Time. CoRR Lorenzo Magnino, Yuchen Zhu, Mathieu Laurière
2024	A	`conf`	Deep Learning for Population-Dependent Controls in Mean Field Control Problems with Common Noise. AAMAS Gökçe Dayanikli, Mathieu Laurière, Jiacheng Zhang
2024	J	`jnl`	Global Solutions to Master Equations for Continuous Time Heterogeneous Agent Macroeconomic Models. CoRR Zhouzhou Gu, Mathieu Laurière, Sebastian Merkel, Jonathan Payne
2024	—	`conf`	How can the tragedy of the commons be prevented?: Introducing Linear Quadratic Mixed Mean Field Games. CDC Gökçe Dayanikli, Mathieu Laurière
2024	J	`jnl`	Independent RL for Cooperative-Competitive Agents: A Mean-Field Perspective. CoRR Muhammad Aneeq uz Zaman, Alec Koppel, Mathieu Laurière, Tamer Basar
2024	A*	`conf`	Learning Discrete-Time Major-Minor Mean Field Games. AAAI Kai Cui, Gökçe Dayanikli, Mathieu Laurière, Matthieu Geist, Olivier Pietquin, Heinz Koeppl
2024	C	`conf`	Multi-population Mean Field Games with Multiple Major Players: Application to Carbon Emission Regulations. ACC Gökçe Dayanikli, Mathieu Laurière
2024	A	`conf`	Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning. AAMAS Zida Wu, Mathieu Laurière, Samuel Jia Cong Chua, Matthieu Geist, Olivier Pietquin, Ankur Mehta
2024	J	`jnl`	Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning. CoRR Zida Wu, Mathieu Laurière, Samuel Jia Cong Chua, Matthieu Geist, Olivier Pietquin, Ankur Mehta
2024	J	`jnl`	Reinforcement Learning for Finite Space Mean-Field Type Games. CoRR Kai Shao, Jiacheng Shen, Chijie An, Mathieu Laurière
2024	J	`jnl`	Robust Cooperative Multi-Agent Reinforcement Learning:A Mean-Field Type Game Perspective. CoRR Muhammad Aneeq uz Zaman, Mathieu Laurière, Alec Koppel, Tamer Basar
2024	—	`conf`	Robust cooperative multi-agent reinforcement learning: A mean-field type game perspective. L4DC Muhammad Aneeq uz Zaman, Mathieu Laurière, Alec Koppel, Tamer Basar
2023	J	`jnl`	Deep Learning for Mean Field Optimal Transport. CoRR Sebastian Baudelet, Brieuc Frénais, Mathieu Laurière, Amal Machtalay, Yuchen Zhu
2023	J	`jnl`	From Nash Equilibrium to Social Optimum and vice versa: a Mean Field Perspective. CoRR René A. Carmona, Gökçe Dayanikli, François Delarue, Mathieu Laurière
2023	J	`jnl`	Learning Discrete-Time Major-Minor Mean Field Games. CoRR Kai Cui, Gökçe Dayanikli, Mathieu Laurière, Matthieu Geist, Olivier Pietquin, Heinz Koeppl
2023	—	`conf`	Machine Learning Architectures for Price Formation Models with Common Noise. CDC Diogo Gomes, Julian Gutierrez, Mathieu Laurière
2023	A*	`conf`	On Imitation in Mean-field Games. NeurIPS Giorgia Ramponi, Pavel Kolev, Olivier Pietquin, Niao He, Mathieu Laurière, Matthieu Geist
2023	J	`jnl`	On Imitation in Mean-field Games. CoRR Giorgia Ramponi, Pavel Kolev, Olivier Pietquin, Niao He, Mathieu Laurière, Matthieu Geist
2023	J	`jnl`	Recent Developments in Machine Learning Methods for Stochastic Control and Games. CoRR Ruimeng Hu, Mathieu Laurière
2023	B	`conf`	The Communication Complexity of Functions with Large Outputs. SIROCCO Lila Fontes, Sophie Laplante, Mathieu Laurière, Alexandre Nolin
2023	J	`jnl`	The communication complexity of functions with large outputs. CoRR Lila Fontes, Sophie Laplante, Mathieu Laurière, Alexandre Nolin
2023	J	`jnl`	The communication complexity of functions with large outputs. Electron. Colloquium Comput. Complex. Lila Fontes, Sophie Laplante, Mathieu Laurière, Alexandre Nolin
2022	A	`conf`	Concave Utility Reinforcement Learning: The Mean-field Game Viewpoint. AAMAS Matthieu Geist, Julien Pérolat, Mathieu Laurière, Romuald Elie, Sarah Perrin, Olivier Bachem, Rémi Munos, Olivier Pietquin
2022	J	`jnl`	Convergence of Large Population Games to Mean Field Games with Interaction Through the Controls. SIAM J. Math. Anal. Mathieu Laurière, Ludovic Tangpi
2022	J	`jnl`	DeepSets and Their Derivative Networks for Solving Symmetric PDEs. J. Sci. Comput. Maximilien Germain, Mathieu Laurière, Huyên Pham, Xavier Warin
2022	J	`jnl`	Finite State Graphon Games with Applications to Epidemics. Dyn. Games Appl. Alexander Aurell, René Carmona, Gökçe Dayanikli, Mathieu Laurière
2022	A*	`conf`	Generalization in Mean Field Games by Learning Master Policies. AAAI Sarah Perrin, Mathieu Laurière, Julien Pérolat, Romuald Élie, Matthieu Geist, Olivier Pietquin
2022	J	`jnl`	Learning Correlated Equilibria in Mean-Field Games. CoRR Paul Muller, Romuald Elie, Mark Rowland, Mathieu Laurière, Julien Pérolat, Sarah Perrin, Matthieu Geist, Georgios Piliouras, Olivier Pietquin, Karl Tuyls
2022	A	`conf`	Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. AAMAS Paul Muller, Mark Rowland, Romuald Elie, Georgios Piliouras, Julien Pérolat, Mathieu Laurière, Raphaël Marinier, Olivier Pietquin, Karl Tuyls
2022	J	`jnl`	Learning Mean Field Games: A Survey. CoRR Mathieu Laurière, Sarah Perrin, Matthieu Geist, Olivier Pietquin
2022	J	`jnl`	Mean Field Models to Regulate Carbon Emissions in Electricity Production. Dyn. Games Appl. René Carmona, Gökçe Dayanikli, Mathieu Laurière
2022	J	`jnl`	Optimal Incentives to Mitigate Epidemics: A Stackelberg Mean Field Game Approach. SIAM J. Control. Optim. Alexander Aurell, René Carmona, Gökçe Dayanikli, Mathieu Laurière
2022	—	`conf`	Reinforcement Learning for Intra-and-Inter-Bank Borrowing and Lending Mean Field Control Game. ICAIF Jimin Lin, Andrea Angiuli, Nils Detering, Jean-Pierre Fouque, Mathieu Laurière
2022	A*	`conf`	Scalable Deep Reinforcement Learning Algorithms for Mean Field Games. ICML Mathieu Laurière, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Pérolat, Romuald Elie, Olivier Pietquin, Matthieu Geist
2022	J	`jnl`	Scalable Deep Reinforcement Learning Algorithms for Mean Field Games. CoRR Mathieu Laurière, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Pérolat, Romuald Élie, Olivier Pietquin, Matthieu Geist
2022	A	`conf`	Scaling Mean Field Games by Online Mirror Descent. AAMAS Julien Pérolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin
2022	A	`conf`	Solving N-Player Dynamic Routing Games with Congestion: A Mean-Field Approach. AAMAS Theophile Cabannes, Mathieu Laurière, Julien Pérolat, Raphaël Marinier, Sertan Girgin, Sarah Perrin, Olivier Pietquin, Alexandre M. Bayen, Eric Goubault, Romuald Elie
2022	J	`jnl`	Stochastic Graphon Games: I. The Static Case. Math. Oper. Res. René Carmona, Daniel B. Cooney, Christy V. Graves, Mathieu Laurière
2022	J	`jnl`	Unified reinforcement Q-learning for mean field game and control problems. Math. Control. Signals Syst. Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière
2021	J	`jnl`	Concave Utility Reinforcement Learning: the Mean-field Game viewpoint. CoRR Matthieu Geist, Julien Pérolat, Mathieu Laurière, Romuald Elie, Sarah Perrin, Olivier Bachem, Rémi Munos, Olivier Pietquin
2021	J	`jnl`	Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games I: The Ergodic Case. SIAM J. Numer. Anal. René Carmona, Mathieu Laurière
2021	J	`jnl`	Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance. CoRR René Carmona, Mathieu Laurière
2021	J	`jnl`	Generalization in Mean Field Games by Learning Master Policies. CoRR Sarah Perrin, Mathieu Laurière, Julien Pérolat, Romuald Élie, Matthieu Geist, Olivier Pietquin
2021	J	`jnl`	Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. CoRR Paul Muller, Mark Rowland, Romuald Elie, Georgios Piliouras, Julien Pérolat, Mathieu Laurière, Raphaël Marinier, Olivier Pietquin, Karl Tuyls
2021	A*	`conf`	Mean Field Games Flock! The Reinforcement Learning Way. IJCAI Sarah Perrin, Mathieu Laurière, Julien Pérolat, Matthieu Geist, Romuald Élie, Olivier Pietquin
2021	J	`jnl`	Mean Field Games Flock! The Reinforcement Learning Way. CoRR Sarah Perrin, Mathieu Laurière, Julien Pérolat, Matthieu Geist, Romuald Élie, Olivier Pietquin
2021	J	`jnl`	Numerical Methods for Mean Field Games and Mean Field Type Control. CoRR Mathieu Laurière
2021	J	`jnl`	Performance of a Markovian neural network versus dynamic programming on a fishing control problem. CoRR Mathieu Laurière, Gilles Pagès, Olivier Pironneau
2021	J	`jnl`	Policy iteration method for time-dependent Mean Field Games systems with non-separable Hamiltonians. CoRR Mathieu Laurière, Jiahao Song, Qing Tang
2021	J	`jnl`	Reinforcement Learning for Mean Field Games, with Applications to Economics. CoRR Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière
2021	J	`jnl`	Scaling up Mean Field Games with Online Mirror Descent. CoRR Julien Pérolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin
2021	J	`jnl`	Solving N-player dynamic routing games with congestion: a mean field approach. CoRR Theophile Cabannes, Mathieu Laurière, Julien Pérolat, Raphaël Marinier, Sertan Girgin, Sarah Perrin, Olivier Pietquin, Alexandre M. Bayen, Éric Goubault, Romuald Elie
2020	J	`jnl`	COVID-19 pandemic control: balancing detection policy and lockdown intervention under ICU sustainability. CoRR Arthur Charpentier, Romuald Elie, Mathieu Laurière, Viet Chi Tran
2020	J	`jnl`	Connecting GANs and MFGs. CoRR Haoyang Cao, Xin Guo, Mathieu Laurière
2020	J	`jnl`	Extended Learning Graphs for Triangle Finding. Algorithmica Titouan Carette, Mathieu Laurière, Frédéric Magniez
2020	A*	`conf`	Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications. NeurIPS Sarah Perrin, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin
2020	J	`jnl`	Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications. CoRR Sarah Perrin, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin
2020	J	`jnl`	Learning a functional control for high-frequency finance. CoRR Laura Leal, Mathieu Laurière, Charles-Albert Lehalle
2020	J	`jnl`	Linear-Quadratic Zero-Sum Mean-Field Type Games: Optimality Conditions and Policy Optimization. CoRR René Carmona, Kenza Hamidouche, Mathieu Laurière, Zongjun Tan
2020	J	`jnl`	Mean Field Games and Applications: Numerical Aspects. CoRR Yves Achdou, Mathieu Laurière
2020	A*	`conf`	On the Convergence of Model Free Learning in Mean Field Games. AAAI Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin
2020	—	`conf`	Policy Optimization for Linear-Quadratic Zero-Sum Mean-Field Type Games. CDC René Carmona, Kenza Hamidouche, Mathieu Laurière, Zongjun Tan
2020	J	`jnl`	Policy Optimization for Linear-Quadratic Zero-Sum Mean-Field Type Games. CoRR René Carmona, Kenza Hamidouche, Mathieu Laurière, Zongjun Tan
2020	J	`jnl`	Unified Reinforcement Q-Learning for Mean Field Game and Control Problems. CoRR Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière
2019	J	`jnl`	Approximate Fictitious Play for Mean Field Games. CoRR Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin
2019	J	`jnl`	Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games: I - The Ergodic Case. CoRR René Carmona, Mathieu Laurière
2019	J	`jnl`	Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games: II - The Finite Horizon Case. CoRR René Carmona, Mathieu Laurière
2019	J	`jnl`	Linear-Quadratic Mean-Field Reinforcement Learning: Convergence of Policy Gradient Methods. CoRR René Carmona, Mathieu Laurière, Zongjun Tan
2019	J	`jnl`	Model-Free Mean-Field Reinforcement Learning: Mean-Field MDP and Mean-Field Q-Learning. CoRR René Carmona, Mathieu Laurière, Zongjun Tan
2019	J	`jnl`	Penalization of Nonsmooth Dynamical Systems with Noise: Ergodicity and Asymptotic Formulae for Threshold Crossings Probabilities. SIAM J. Appl. Dyn. Syst. Mathieu Laurière, Laurent Mertz
2018	J	`jnl`	Asymptotic formulae for the risk of failure related to an elasto-plastic problem with noise. Asymptot. Anal. Cyril Feau, Mathieu Laurière, Laurent Mertz
2018	J	`jnl`	Robust Bell inequalities from communication complexity. Quantum Sophie Laplante, Mathieu Laurière, Alexandre Nolin, Jérémie Roland, Gabriel Senno
2017	A	`conf`	Extended Learning Graphs for Triangle Finding. STACS Titouan Carette, Mathieu Laurière, Frédéric Magniez
2017	A	`conf`	The Flow of Information in Interactive Quantum Protocols: the Cost of Forgetting. ITCS Mathieu Laurière, Dave Touchette
2017	J	`jnl`	The Flow of Information in Interactive Quantum Protocols: the Cost of Forgetting. CoRR Mathieu Laurière, Dave Touchette
2016	J	`jnl`	Dynamic Programming for Mean-Field Type Control. J. Optim. Theory Appl. Mathieu Laurière, Olivier Pironneau
2016	J	`jnl`	Extended Learning Graphs for Triangle Finding. CoRR Titouan Carette, Mathieu Laurière, Frédéric Magniez
2016	J	`jnl`	Information cost of quantum communication protocols. Quantum Inf. Comput. Iordanis Kerenidis, Mathieu Laurière, Francois Le Gall, Mathys Rennela
2016	J	`jnl`	Mean Field Type Control with Congestion (II): An Augmented Lagrangian Method. CoRR Yves Achdou, Mathieu Laurière
2016	J	`jnl`	Relative Discrepancy Does Not Separate Information and Communication Complexity. ACM Trans. Comput. Theory Lila Fontes, Rahul Jain, Iordanis Kerenidis, Sophie Laplante, Mathieu Laurière, Jérémie Roland
2016	—	`conf`	Robust Bell Inequalities from Communication Complexity. TQC Sophie Laplante, Mathieu Laurière, Alexandre Nolin, Jérémie Roland, Gabriel Senno
2016	J	`jnl`	Robust Bell inequalities from communication complexity. CoRR Sophie Laplante, Mathieu Laurière, Alexandre Nolin, Jérémie Roland, Gabriel Senno
2016	—	`conf`	The problem of musical gesture continuation and a baseline system. ICMC Charles Bascou, Valentin Emiya, Mathieu Laurière
2015	—	`conf`	Relative Discrepancy Does not Separate Information and Communication Complexity. ICALP (1) Lila Fontes, Rahul Jain, Iordanis Kerenidis, Sophie Laplante, Mathieu Laurière, Jérémie Roland
2015	J	`jnl`	Relative Discrepancy does not separate Information and Communication Complexity. Electron. Colloquium Comput. Complex. Lila Fontes, Rahul Jain, Iordanis Kerenidis, Sophie Laplante, Mathieu Laurière, Jérémie Roland
2014	J	`jnl`	Privacy in Quantum Communication Complexity. CoRR Iordanis Kerenidis, Mathieu Laurière, François Le Gall, Mathys Rennela
2013	—	`conf`	New Lower Bounds for Privacy in Communication Protocols. ICITS Iordanis Kerenidis, Mathieu Laurière, David Xiao
2013	J	`jnl`	New lower bounds for privacy in communication protocols. Electron. Colloquium Comput. Complex. Iordanis Kerenidis, Mathieu Laurière, David Xiao