Deep neural networks algorithms for stochastic control problems on finite horizon: convergence analysis

11 December 2018

Papers citing "Deep neural networks algorithms for stochastic control problems on finite horizon: convergence analysis"

11 / 11 papers shown

Title
Solving Finite-Horizon MDPs via Low-Rank Tensors Sergio Rozada Jose Luis Orejuela Antonio G. Marques 73 0 0 17 Jan 2025
Reinforcement learning Florentin Wörgötter 82 2,536 0 16 May 2024
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 52 2 0 08 Apr 2024
Full error analysis for the training of deep neural networks C. Beck Arnulf Jentzen Benno Kuckuck 43 47 0 30 Sep 2019
Deep neural networks algorithms for stochastic control problems on finite horizon: numerical applications Achref Bachouch Côme Huré N. Langrené H. Pham 59 86 0 13 Dec 2018
Convergence of the Deep BSDE Method for Coupled FBSDEs Jiequn Han Jihao Long 57 159 0 03 Nov 2018
Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations Weinan E Jiequn Han Arnulf Jentzen 119 797 0 15 Jun 2017
Deep Reinforcement Learning: An Overview Yuxi Li OffRL VLM 155 1,535 0 25 Jan 2017
EM Algorithm and Stochastic Control in Economics S. Kou X. Peng Xingbo Xu 32 5 0 06 Nov 2016
Deep Learning Approximation for Stochastic Control Problems Jiequn Han E. Weinan BDL 49 194 0 02 Nov 2016
Breaking the Curse of Dimensionality with Convex Neural Networks Francis R. Bach 180 706 0 30 Dec 2014