20 citations · 40 across the 7 of their papers we have counts for
4 papers · 1 filter
Numerical methods for Mean field Games based on Gaussian Processes and Fourier Features
Chenchen Mou, Xianjin Yang, Chao Zhou
In this article, we propose two numerical methods, the Gaussian Process (GP) method and the Fourier Features (FF) algorithm, to solve mean field games (MFGs). The GP algorithm appr…
Robust lEarned Shrinkage-Thresholding (REST): Robust unrolling for sparse recover
Wei Pu, Chao Zhou, Yonina C. Eldar +1
In this paper, we consider deep neural networks for solving inverse problems that are robust to forward model mis-specifications. Specifically, we treat sensing problems with model…
The Discovery of Dynamics via Linear Multistep Methods and Deep Learning: Error Estimation
Qiang Du, Yiqi Gu, Haizhao Yang +1
Identifying hidden dynamics from observed data is a significant and challenging task in a wide range of applications. Recently, the combination of linear multistep methods (LMMs) a…
A learning scheme by sparse grids and Picard approximations for semilinear parabolic PDEs
Jean-François Chassagneux, Junchao Chen, Noufel Frikha +1
Relying on the classical connection between Backward Stochastic Differential Equations (BSDEs) and non-linear parabolic partial differential equations (PDEs), we propose a new prob…