Deep neural networks algorithms for stochastic control problems on finite horizon: numerical applications

13 December 2018

Papers citing "Deep neural networks algorithms for stochastic control problems on finite horizon: numerical applications"

8 / 8 papers shown

Title
Convergence analysis of controlled particle systems arising in deep learning: from finite to infinite sample size Huafu Liao Alpár R. Mészáros Chenchen Mou Chao Zhou 26 2 0 08 Apr 2024
Langevin algorithms for Markovian Neural Networks and Deep Stochastic control Pierre Bras Gilles Pagès 22 3 0 22 Dec 2022
SympOCnet: Solving optimal control problems with applications to high-dimensional multi-agent path planning problems Tingwei Meng Zhen Zhang Jérome Darbon George Karniadakis 16 15 0 14 Jan 2022
Performance of a Markovian neural network versus dynamic programming on a fishing control problem Mathieu Laurière Gilles Pagès O. Pironneau 11 5 0 14 Sep 2021
Neural network architectures using min-plus algebra for solving certain high dimensional optimal control problems and Hamilton-Jacobi PDEs Jérome Darbon P. Dower Tingwei Meng 8 22 0 07 May 2021
Solving stochastic optimal control problem via stochastic maximum principle with deep learning method Shaolin Ji S. Peng Ying Peng Xichuan Zhang 16 13 0 05 Jul 2020
Deep Fictitious Play for Stochastic Differential Games Ruimeng Hu 19 29 0 22 Mar 2019
Deep neural networks algorithms for stochastic control problems on finite horizon: convergence analysis Côme Huré H. Pham Achref Bachouch N. Langrené 13 64 0 11 Dec 2018