Three algorithms for solving high-dimensional fully-coupled FBSDEs through deep learning
Numerical Analysis
2020-02-04 v4 Machine Learning
Numerical Analysis
Probability
Abstract
Recently, the deep learning method has been used for solving forward-backward stochastic differential equations (FBSDEs) and parabolic partial differential equations (PDEs). It has good accuracy and performance for high-dimensional problems. In this paper, we mainly solve fully coupled FBSDEs through deep learning and provide three algorithms. Several numerical results show remarkable performance especially for high-dimensional cases.
Cite
@article{arxiv.1907.05327,
title = {Three algorithms for solving high-dimensional fully-coupled FBSDEs through deep learning},
author = {Shaolin Ji and Shige Peng and Ying Peng and Xichuan Zhang},
journal= {arXiv preprint arXiv:1907.05327},
year = {2020}
}
Comments
24 pages, 7 figures