4 citations · 5 across the 4 of their papers we have counts for
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A Posteriori Error Analysis for Decoupled Neural Approximations of Fully Coupled FBSDEs with Control Mismatch
Xichuan Zhang
This paper develops an a posteriori error analysis framework for decoupled neural approximations of fully coupled forward--backward stochastic differential equations (FBSDEs). It p…
A deep learning method for solving stochastic optimal control problems driven by fully-coupled FBSDEs
Shaolin Ji, Shige Peng, Ying Peng +1
In this paper,we mainly focus on the numerical solution of high-dimensional stochastic optimal control problem driven by fully-coupled forward-backward stochastic differential equa…
A novel control method for solving high-dimensional Hamiltonian systems through deep neural networks
Shaolin Ji, Shige Peng, Ying Peng +1
In this paper, we mainly focus on solving high-dimensional stochastic Hamiltonian systems with boundary condition, which is essentially a Forward Backward Stochastic Differential E…
Solving stochastic optimal control problem via stochastic maximum principle with deep learning method
Shaolin Ji, Shige Peng, Ying Peng +1
In this paper, we aim to solve the high dimensional stochastic optimal control problem from the view of the stochastic maximum principle via deep learning. By introducing the exten…