1 citations · 1 across the 7 of their papers we have counts for
9 papers
Master Equations for Mean Field Game of Controls: A Unification of Weak Solution Notions
Mengzhen Li, Xintian Liu, Chenchen Mou +1
In this manuscript, we study the master equation for mean field game of controls, assuming only that the data are Lipschitz continuous in the measure variable. Accordingly, we prop…
Robust mean field control: an application to optimal execution under composite uncertainty
Huafu Liao, Shuhui Liu, Chenchen Mou +1
We provide a framework for robust mean field control problems that describe multi-dimensional optimal liquidation problems under uncertainty from both the underlying stochastic pro…
Local well-posedness of general mean field game master equations
Chenchen Mou, Jianfeng Zhang, Jianjun Zhou
This paper presents a generic approach for establishing mean field game master equations, applicable whenever the mean field equilibrium can be characterized by a McKean-Vlasov for…
The global well-posedness for master equations of mean field games of controls
Shuhui Liu, Xintian Liu, Chenchen Mou +1
In this manuscript, we establish the global well-posedness for master equations of mean field games of controls, where the interaction is through the joint law of the state and con…
Finite difference schemes for Hamilton--Jacobi equation on Wasserstein space on graphs
Jianbo Cui, Tonghe Dang, Chenchen Mou
This work proposes and studies numerical schemes for initial value problems of Hamilton--Jacobi equations (HJEs) with a graph individual noise on the Wasserstein space on graphs. N…
Learning Surrogate Potential Mean Field Games via Gaussian Processes: A Data-Driven Approach to Ill-Posed Inverse Problems
Jingguo Zhang, Xianjin Yang, Chenchen Mou +1
Mean field games (MFGs) describe the collective behavior of large populations of interacting agents. In this work, we tackle ill-posed inverse problems in potential MFGs, aiming to…
Convergence analysis of controlled particle systems arising in deep learning: from finite to infinite sample size
Huafu Liao, Alpár R. Mészáros, Chenchen Mou +1
This paper deals with a class of neural SDEs and studies the limiting behavior of the associated sampled optimal control problems as the sample size grows to infinity. The neural S…
Decoding Mean Field Games from Population and Environment Observations By Gaussian Processes
Jinyan Guo, Chenchen Mou, Xianjin Yang +1
This paper presents a Gaussian Process (GP) framework, a non-parametric technique widely acknowledged for regression and classification tasks, to address inverse problems in mean f…
Linear-Quadratic Mean Field Control with Non-Convex Data
Mengzhen Li, Chenchen Mou, Zhen Wu +1
In this manuscript, we study a class of linear-quadratic (LQ) mean field control problems with a common noise and their corresponding -particle systems. The mean field control p…