Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1908.01613
Cited By
v1
v2 (latest)
Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games: II -- The Finite Horizon Case
The Annals of Applied Probability (AAP), 2019
5 August 2019
René Carmona
Mathieu Laurière
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games: II -- The Finite Horizon Case"
41 / 41 papers shown
Simultaneously Solving Infinitely Many LQ Mean Field Games In Hilbert Spaces: The Power of Neural Operators
Dena Firoozi
Anastasis Kratsios
Xuwei Yang
168
4
0
22 Oct 2025
Error analysis for the deep Kolmogorov method
Iulian Cîmpean
Thang Do
Lukas Gonon
Arnulf Jentzen
Ionel Popescu
214
0
0
23 Aug 2025
A brief review of the Deep BSDE method for solving high-dimensional partial differential equations
Jiequn Han
Arnulf Jentzen
Weinan E
AI4CE
313
6
0
07 May 2025
Gaussian process policy iteration with additive Schwarz acceleration for forward and inverse HJB and mean field game problems
Xianjin Yang
Jingguo Zhang
223
2
0
01 May 2025
Neural Mean-Field Games: Extending Mean-Field Game Theory with Neural Stochastic Differential Equations
Anna C. M. Thöni
Yoram Bachrach
Tal Kachman
430
0
0
17 Apr 2025
Score-based Neural Ordinary Differential Equations for Computing Mean Field Control Problems
Journal of Computational Physics (JCP), 2024
Mo Zhou
Stanley Osher
Wuchen Li
370
7
0
24 Sep 2024
Mean-field Chaos Diffusion Models
International Conference on Machine Learning (ICML), 2024
S. Park
Dongjun Kim
Ahmed Alaa
DiffM
292
1
0
08 Jun 2024
Deep Backward and Galerkin Methods for the Finite State Master Equation
Asaf Cohen
Mathieu Lauriere
Ethan C. Zell
276
5
0
08 Mar 2024
A Deep Learning Method for Optimal Investment Under Relative Performance Criteria Among Heterogeneous Agents
European Journal of Operational Research (EJOR), 2024
Mathieu Laurière
Ludovic Tangpi
Xuchen Zhou
260
3
0
12 Feb 2024
Decoding Mean Field Games from Population and Environment Observations By Gaussian Processes
Journal of Computational Physics (JCP), 2023
Jinyan Guo
Chenchen Mou
Xianjin Yang
Chao Zhou
AI4CE
347
9
0
08 Dec 2023
Stochastic Optimal Control Matching
Neural Information Processing Systems (NeurIPS), 2023
Carles Domingo-Enrich
Jiequn Han
Brandon Amos
Joan Bruna
Ricky T. Q. Chen
DiffM
420
34
0
04 Dec 2023
Policy Gradient Optimal Correlation Search for Variance Reduction in Monte Carlo simulation and Maximum Optimal Transport
Pierre Bras
Gilles Pagès
230
1
0
24 Jul 2023
Actor-Critic learning for mean-field control in continuous time
N. Frikha
Maximilien Germain
Mathieu Laurière
H. Pham
Xuan Song
229
25
0
13 Mar 2023
Deep Learning for Mean Field Optimal Transport
ESAIM Proceedings and Surveys (ESAIM Proc. Surv.), 2023
Sebastian Baudelet
Brieuc Frénais
Mathieu Laurière
Amal Machtalay
Yuchen Zhu
OT
168
3
0
28 Feb 2023
A Policy Gradient Framework for Stochastic Optimal Control Problems with Global Convergence Guarantee
SIAM Journal of Control and Optimization (SICON), 2023
Mo Zhou
Jian-Xiong Lu
348
12
0
11 Feb 2023
Langevin algorithms for Markovian Neural Networks and Deep Stochastic control
IEEE International Joint Conference on Neural Network (IJCNN), 2022
Pierre Bras
Gilles Pagès
247
6
0
22 Dec 2022
Stability Via Adversarial Training of Neural Network Stochastic Control of Mean-Field Type
IEEE Conference on Decision and Control (CDC), 2022
J. Barreiro‐Gomez
S. E. Choutri
Boualem Djehiche
OOD
AAML
94
2
0
27 Sep 2022
Deep Generalized Schrödinger Bridge
Neural Information Processing Systems (NeurIPS), 2022
Guan-Horng Liu
T. Chen
Oswin So
Evangelos A. Theodorou
OT
AI4CE
376
56
0
20 Sep 2022
A Forward Propagation Algorithm for Online Optimization of Nonlinear Stochastic Differential Equations
Ziheng Wang
Justin A. Sirignano
276
4
0
10 Jul 2022
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games
International Conference on Machine Learning (ICML), 2022
Mathieu Laurière
Sarah Perrin
Sertan Girgin
Paul Muller
Ayush Jain
...
Georgios Piliouras
Julien Pérolat
Romuald Élie
Olivier Pietquin
Matthieu Geist
279
61
0
22 Mar 2022
DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method
Journal of Computational Physics (JCP), 2021
Zhongjian Wang
Jack Xin
Zhiwen Zhang
398
20
0
02 Nov 2021
Deep Learning for Principal-Agent Mean Field Games
S. Campbell
Yichao Chen
Arvind Shrivats
S. Jaimungal
255
18
0
03 Oct 2021
Generalization in Mean Field Games by Learning Master Policies
Sarah Perrin
Mathieu Laurière
Julien Pérolat
Romuald Élie
Matthieu Geist
Olivier Pietquin
AI4CE
261
46
0
20 Sep 2021
Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance
René Carmona
Mathieu Laurière
AI4CE
241
35
0
09 Jul 2021
Exploration noise for learning linear-quadratic mean field games
François Delarue
A. Vasileiadis
MLT
275
14
0
02 Jul 2021
Reinforcement Learning for Mean Field Games, with Applications to Economics
Andrea Angiuli
J. Fouque
Mathieu Lauriere
242
32
0
25 Jun 2021
Random feature neural networks learn Black-Scholes type PDEs without curse of dimensionality
Journal of machine learning research (JMLR), 2021
Lukas Gonon
237
48
0
14 Jun 2021
Signatured Deep Fictitious Play for Mean Field Games with Common Noise
International Conference on Machine Learning (ICML), 2021
Ming Min
Ruimeng Hu
179
30
0
06 Jun 2021
Scaling up Mean Field Games with Online Mirror Descent
Julien Perolat
Sarah Perrin
Romuald Elie
Mathieu Laurière
Georgios Piliouras
Matthieu Geist
K. Tuyls
Olivier Pietquin
LRM
AI4CE
303
54
0
28 Feb 2021
An overview on deep learning-based approximation methods for partial differential equations
C. Beck
Martin Hutzenthaler
Arnulf Jentzen
Benno Kuckuck
670
175
0
22 Dec 2020
Linear-Quadratic Zero-Sum Mean-Field Type Games: Optimality Conditions and Policy Optimization
Journal of Dynamics & Games (JDG), 2020
René Carmona
Kenza Hamidouche
Mathieu Laurière
Zongjun Tan
231
11
0
01 Sep 2020
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications
Sarah Perrin
Julien Perolat
Mathieu Laurière
Matthieu Geist
Romuald Elie
Olivier Pietquin
370
138
0
05 Jul 2020
Solving stochastic optimal control problem via stochastic maximum principle with deep learning method
Shaolin Ji
S. Peng
Ying Peng
Xichuan Zhang
455
25
0
05 Jul 2020
Unified Reinforcement Q-Learning for Mean Field Game and Control Problems
MCSS. Mathematics of Control, Signals and Systems (MCSS), 2020
Andrea Angiuli
J. Fouque
Mathieu Laurière
459
90
0
24 Jun 2020
Learning a functional control for high-frequency finance
Laura Leal
Mathieu Laurière
Charles-Albert Lehalle
AIFin
168
23
0
17 Jun 2020
Gradient Flows for Regularized Stochastic Control Problems
SIAM Journal of Control and Optimization (SICON), 2020
David Siska
Lukasz Szpruch
438
21
0
10 Jun 2020
Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space
Nikolas Nusken
Lorenz Richter
AI4CE
337
148
0
11 May 2020
A Mean Field Games model for finite mixtures of Bernoulli and Categorical distributions
Laura Aquilanti
S. Cacace
F. Camilli
Raul De Maio
94
0
0
17 Apr 2020
Connecting GANs, MFGs, and OT
SIAM Journal on Applied Mathematics (SIAM J. Appl. Math.), 2020
Haoyang Cao
Xin Guo
Mathieu Laurière
GAN
492
14
0
10 Feb 2020
A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2019
Lars Ruthotto
Stanley Osher
Wuchen Li
L. Nurbekyan
Samy Wu Fung
AI4CE
443
271
0
04 Dec 2019
Model-Free Mean-Field Reinforcement Learning: Mean-Field MDP and Mean-Field Q-Learning
The Annals of Applied Probability (AAP), 2019
René Carmona
Mathieu Laurière
Zongjun Tan
OffRL
236
121
0
28 Oct 2019
1
Page 1 of 1