Deep Learning Approximation for Stochastic Control Problems

2 November 2016

Papers citing "Deep Learning Approximation for Stochastic Control Problems"

35 / 35 papers shown

Title
In-Context Operator Learning for Linear Propagator Models Tingwei Meng Moritz Voß Nils Detering Giulio Farolfi Stanley Osher Georg Menz 41 0 0 28 Jan 2025
An Efficient On-Policy Deep Learning Framework for Stochastic Optimal Control Mengjian Hua Matthieu Laurière Eric Vanden-Eijnden 39 3 0 07 Oct 2024
Online Control-Informed Learning Zihao Liang Tianyu Zhou Zehui Lu Shaoshuai Mou 33 1 0 04 Oct 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 26 2 0 08 Apr 2024
Learning Free Terminal Time Optimal Closed-loop Control of Manipulators Wei Hu Yue Zhao E. Weinan Jiequn Han Jihao Long 22 0 0 29 Nov 2023
Stochastic Delay Differential Games: Financial Modeling and Machine Learning Algorithms R. Balkin Héctor D. Ceniceros Ruimeng Hu 21 2 0 12 Jul 2023
Neural Partial Differential Equations with Functional Convolution Z. Wu Xingzhe He Yijun Li Cheng Yang Rui Liu S. Xiong Bo Zhu 23 1 0 10 Mar 2023
Langevin algorithms for Markovian Neural Networks and Deep Stochastic control Pierre Bras Gilles Pagès 30 3 0 22 Dec 2022
Deep learning for gradient flows using the Brezis-Ekeland principle Laura Carini Max Jensen R. Nürnberg 21 0 0 28 Sep 2022
Finite Expression Method for Solving High-Dimensional Partial Differential Equations Senwei Liang Haizhao Yang 34 18 0 21 Jun 2022
Neural Network Optimal Feedback Control with Guaranteed Local Stability Tenavi Nakamura-Zimmerer Q. Gong W. Kang 20 9 0 01 May 2022
On Parametric Optimal Execution and Machine Learning Surrogates Tao Chen M. Ludkovski Moritz Voß 21 1 0 18 Apr 2022
Linear convergence of a policy gradient method for some finite horizon continuous time control problems C. Reisinger Wolfgang Stockinger Yufei Zhang 16 5 0 22 Mar 2022
Convergence of a robust deep FBSDE method for stochastic control Kristoffer Andersson Adam Andersson C. Oosterlee 34 19 0 18 Jan 2022
The Parametric Cost Function Approximation: A new approach for multistage stochastic programming Warrren B Powell Saeed Ghadimi 19 7 0 01 Jan 2022
Data-Driven Computational Methods for the Domain of Attraction and Zubov's Equation W. Kang Kai Sun Liang Xu 20 13 0 29 Dec 2021
A novel control method for solving high-dimensional Hamiltonian systems through deep neural networks Shaolin Ji S. Peng Ying Peng Xichuan Zhang 19 1 0 04 Nov 2021
Performance of a Markovian neural network versus dynamic programming on a fishing control problem Mathieu Laurière Gilles Pagès O. Pironneau 17 5 0 14 Sep 2021
Data-informed Deep Optimization Lulu Zhang Z. Xu Yaoyu Zhang AI4CE 35 3 0 17 Jul 2021
Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance René Carmona Mathieu Laurière AI4CE 20 26 0 09 Jul 2021
Machine Learning and Computational Mathematics Weinan E PINN AI4CE 32 61 0 23 Sep 2020
Convergence of Deep Fictitious Play for Stochastic Differential Games Jiequn Han Ruimeng Hu Jihao Long 19 19 0 12 Aug 2020
Expressivity of Deep Neural Networks Ingo Gühring Mones Raslan Gitta Kutyniok 16 51 0 09 Jul 2020
Solving stochastic optimal control problem via stochastic maximum principle with deep learning method Shaolin Ji S. Peng Ying Peng Xichuan Zhang 24 13 0 05 Jul 2020
Machine Learning and Control Theory A. Bensoussan Yiqun Li Dinh Phan Cao Nguyen M. Tran S. Yam Xiang Zhou AI4CE 32 12 0 10 Jun 2020
Machine Learning from a Continuous Viewpoint E. Weinan Chao Ma Lei Wu 33 102 0 30 Dec 2019
Multi-scale Deep Neural Networks for Solving High Dimensional PDEs Wei Cai Zhi-Qin John Xu AI4CE 19 38 0 25 Oct 2019
Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games: II -- The Finite Horizon Case René Carmona Mathieu Laurière 11 94 0 05 Aug 2019
Deep Forward-Backward SDEs for Min-max Control Ziyi Wang Keuntaek Lee M. Pereira Ioannis Exarchos Evangelos A. Theodorou 19 14 0 11 Jun 2019
A neural network based policy iteration algorithm with global $H^2$ -superlinear convergence for stochastic games on domains Kazufumi Ito C. Reisinger Yufei Zhang 14 27 0 05 Jun 2019
Deep Fictitious Play for Stochastic Differential Games Ruimeng Hu 25 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
Monge-Ampère Flow for Generative Modeling Linfeng Zhang E. Weinan Lei Wang DRL 17 62 0 26 Sep 2018
Machine Learning for semi linear PDEs Quentin Chan-Wai-Nam Joseph Mikael X. Warin ODL 21 111 0 20 Sep 2018
Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations Weinan E Jiequn Han Arnulf Jentzen 18 780 0 15 Jun 2017