no code implementations • 8 Apr 2024 • Huafu Liao, Alpár R. Mészáros, Chenchen Mou, Chao Zhou
Using these uniform regularity results, we show the convergence of the minima of objective functionals and optimal parameters of the neural SDEs as the sample size N tends to infinity.
no code implementations • 8 Dec 2023 • Jinyan Guo, Chenchen Mou, Xianjin Yang, Chao Zhou
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 field games (MFGs).
no code implementations • 29 Jan 2021 • Wilfrid Gangbo, Alpár R. Mészáros, Chenchen Mou, Jianfeng Zhang
In this manuscript, we propose a structural condition on non-separable Hamiltonians, which we term displacement monotonicity condition, to study second order mean field games master equations.
Analysis of PDEs Optimization and Control Probability 35R15, 49N80, 49Q22, 60H30, 91A16, 93E20