Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games: II -- The Finite Horizon Case

5 August 2019

Mathieu Laurière

Papers citing "Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games: II -- The Finite Horizon Case"

20 / 20 papers shown

Title
Gaussian Process Policy Iteration with Additive Schwarz Acceleration for Forward and Inverse HJB and Mean Field Game Problems Xianjin Yang Jingguo Zhang 24 0 0 01 May 2025
Modelling Mean-Field Games with Neural Ordinary Differential Equations Anna C. M. Thöni Yoram Bachrach Tal Kachman 38 0 0 17 Apr 2025
Score-based Neural Ordinary Differential Equations for Computing Mean Field Control Problems Mo Zhou Stanley Osher Wuchen Li 92 3 0 24 Sep 2024
Stochastic Optimal Control Matching Carles Domingo-Enrich Jiequn Han Brandon Amos Joan Bruna Ricky T. Q. Chen DiffM 20 7 0 04 Dec 2023
Deep Learning for Mean Field Optimal Transport Sebastian Baudelet Brieuc Frénais Mathieu Laurière Amal Machtalay Yuchen Zhu OT 28 2 0 28 Feb 2023
A Policy Gradient Framework for Stochastic Optimal Control Problems with Global Convergence Guarantee Mo Zhou Jian-Xiong Lu 38 7 0 11 Feb 2023
Langevin algorithms for Markovian Neural Networks and Deep Stochastic control Pierre Bras Gilles Pagès 30 3 0 22 Dec 2022
Deep Generalized Schrödinger Bridge Guan-Horng Liu T. Chen Oswin So Evangelos A. Theodorou OT AI4CE 16 35 0 20 Sep 2022
DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method Zhongjian Wang Jack Xin Zhiwen Zhang 39 15 0 02 Nov 2021
Deep Learning for Principal-Agent Mean Field Games S. Campbell Yichao Chen Arvind Shrivats S. Jaimungal 29 16 0 03 Oct 2021
Generalization in Mean Field Games by Learning Master Policies Sarah Perrin Mathieu Laurière Julien Pérolat Romuald Élie M. Geist Olivier Pietquin AI4CE 94 35 0 20 Sep 2021
Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance René Carmona Mathieu Laurière AI4CE 25 26 0 09 Jul 2021
Exploration noise for learning linear-quadratic mean field games François Delarue A. Vasileiadis MLT 34 11 0 02 Jul 2021
Random feature neural networks learn Black-Scholes type PDEs without curse of dimensionality Lukas Gonon 26 35 0 14 Jun 2021
Scaling up Mean Field Games with Online Mirror Descent Julien Perolat Sarah Perrin Romuald Elie Mathieu Laurière Georgios Piliouras M. Geist K. Tuyls Olivier Pietquin LRM AI4CE 66 45 0 28 Feb 2021
An overview on deep learning-based approximation methods for partial differential equations C. Beck Martin Hutzenthaler Arnulf Jentzen Benno Kuckuck 35 146 0 22 Dec 2020
Solving stochastic optimal control problem via stochastic maximum principle with deep learning method Shaolin Ji S. Peng Ying Peng Xichuan Zhang 29 14 0 05 Jul 2020
Gradient Flows for Regularized Stochastic Control Problems David Siska Lukasz Szpruch 26 20 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 38 105 0 11 May 2020
Model-Free Mean-Field Reinforcement Learning: Mean-Field MDP and Mean-Field Q-Learning René Carmona Mathieu Laurière Zongjun Tan OffRL 34 97 0 28 Oct 2019