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Journal Articles
- 2024
[j9]Jiequn Han, Ruimeng Hu
, Jihao Long:
Learning High-Dimensional McKean-Vlasov Forward-Backward Stochastic Differential Equations with General Distribution Dependence. SIAM J. Numer. Anal. 62(1): 1-24 (2024)- 2023
- [j8]Chengfan Gao, Siping Gao, Ruimeng Hu, Zimu Zhu:
Convergence of the Backward Deep BSDE Method with Applications to Optimal Stopping Problems. SIAM J. Financial Math. 14(4): 1290-1303 (2023) - 2022
- [j7]Jean-Pierre Fouque, Ruimeng Hu, Ronnie Sircar:
Sub- and Supersolution Approach to Accuracy Analysis of Portfolio Optimization Asymptotics in Multiscale Stochastic Factor Markets. SIAM J. Financial Math. 13(1): 109-128 (2022) - 2021
- [j6]Jiequn Han, Ruimeng Hu:
Recurrent neural networks for stochastic control problems with delay. Math. Control. Signals Syst. 33(4): 775-795 (2021) - 2020
- [j5]Jean-Pierre Fouque, Ruimeng Hu:
Multiscale Asymptotic Analysis for Portfolio Optimization under Stochastic Environment. Multiscale Model. Simul. 18(3): 1318-1342 (2020) - 2018
- [j4]Zhenyu Cui, Qi Feng, Ruimeng Hu, Bin Zou:
Systemic risk and optimal fee for central clearing counterparty under partial netting. Oper. Res. Lett. 46(3): 306-311 (2018) - [j3]Jean-Pierre Fouque, Ruimeng Hu:
Optimal Portfolio under Fast Mean-Reverting Fractional Stochastic Environment. SIAM J. Financial Math. 9(2): 564-601 (2018) - 2017
- [j2]Ruimeng Hu, Mike Ludkovski:
Sequential Design for Ranking Response Surfaces. SIAM/ASA J. Uncertain. Quantification 5(1): 212-239 (2017) - [j1]Jean-Pierre Fouque, Ruimeng Hu:
Asymptotic Optimal Strategy for Portfolio Optimization in a Slowly Varying Stochastic Environment. SIAM J. Control. Optim. 55(3): 1990-2023 (2017)
Conference and Workshop Papers
- 2023
- [c5]Ming Min, Ruimeng Hu, Tomoyuki Ichiba:
Directed Chain Generative Adversarial Networks. ICML 2023: 24812-24830 - 2021
- [c4]Ming Min, Ruimeng Hu:
Signatured Deep Fictitious Play for Mean Field Games with Common Noise. ICML 2021: 7736-7747 - [c3]Yao Xuan, Robert Balkin, Jiequn Han, Ruimeng Hu, Héctor D. Ceniceros:
Optimal Policies for a Pandemic: A Stochastic Game Approach and a Deep Learning Algorithm. MSML 2021: 987-1012 - 2020
- [c2]Jiequn Han, Ruimeng Hu:
Deep Fictitious Play for Finding Markovian Nash Equilibrium in Multi-Agent Games. MSML 2020: 221-245 - 2018
- [c1]Ruimeng Hu:
Asymptotic Optimal Portfolio in Fast Mean-Reverting Stochastic Environments. CDC 2018: 5771-5776
Editorship
- 2022
- [e1]Daniele Magazzeni, Senthil Kumar, Rahul Savani, Renyuan Xu, Carmine Ventre, Blanka Horvath, Ruimeng Hu, Tucker Balch, Francesca Toni:
3rd ACM International Conference on AI in Finance, ICAIF 2022, New York, NY, USA, November 2-4, 2022. ACM 2022, ISBN 978-1-4503-9376-8 [contents]
Informal and Other Publications
- 2024
- [i19]Elie Abdo, Ruimeng Hu, Quyuan Lin:
Accuracy Analysis of Physics-Informed Neural Networks for Approximating the Critical SQG Equation. CoRR abs/2401.10879 (2024) - [i18]Elie Abdo, Lihui Chai, Ruimeng Hu, Xu Yang:
Error estimates of physics-informed neural networks for approximating Boltzmann equation. CoRR abs/2407.08383 (2024) - 2023
- [i17]Ruimeng Hu, Mathieu Laurière:
Recent Developments in Machine Learning Methods for Stochastic Control and Games. CoRR abs/2303.10257 (2023) - [i16]Ming Min, Ruimeng Hu, Tomoyuki Ichiba:
Directed Chain Generative Adversarial Networks. CoRR abs/2304.13131 (2023) - [i15]Robert Balkin, Héctor D. Ceniceros, Ruimeng Hu:
Stochastic Delay Differential Games: Financial Modeling and Machine Learning Algorithms. CoRR abs/2307.06450 (2023) - [i14]Andrea Angiuli, Jean-Pierre Fouque, Ruimeng Hu, Alan Raydan:
Deep Reinforcement Learning for Infinite Horizon Mean Field Problems in Continuous Spaces. CoRR abs/2309.10953 (2023) - [i13]Michael Barnett, William Brock, Lars Peter Hansen, Ruimeng Hu, Joseph Huang:
A Deep Learning Analysis of Climate Change, Innovation, and Uncertainty. CoRR abs/2310.13200 (2023) - 2022
- [i12]Jiequn Han, Ruimeng Hu, Jihao Long:
Learning High-Dimensional McKean-Vlasov Forward-Backward Stochastic Differential Equations with General Distribution Dependence. CoRR abs/2204.11924 (2022) - [i11]Yao Xuan, Robert Balkin, Jiequn Han, Ruimeng Hu, Héctor D. Ceniceros:
Pandemic Control, Game Theory and Machine Learning. CoRR abs/2208.08646 (2022) - [i10]Ruimeng Hu, Quyuan Lin, Alan Raydan, Sui Tang:
Higher-Order Error estimates for physics-informed neural networks approximating the primitive equations. CoRR abs/2209.11929 (2022) - [i9]Chengfan Gao, Siping Gao, Ruimeng Hu, Zimu Zhu:
Convergence of the Backward Deep BSDE Method with Applications to Optimal Stopping Problems. CoRR abs/2210.04118 (2022) - 2021
- [i8]Jiequn Han, Ruimeng Hu:
Recurrent Neural Networks for Stochastic Control Problems with Delay. CoRR abs/2101.01385 (2021) - [i7]Jiequn Han, Ruimeng Hu, Jihao Long:
A Class of Dimensionality-free Metrics for the Convergence of Empirical Measures. CoRR abs/2104.12036 (2021) - [i6]Ming Min, Ruimeng Hu:
Signatured Deep Fictitious Play for Mean Field Games with Common Noise. CoRR abs/2106.03272 (2021) - 2020
- [i5]Jiequn Han, Ruimeng Hu, Jihao Long:
Convergence of Deep Fictitious Play for Stochastic Differential Games. CoRR abs/2008.05519 (2020) - [i4]Yao Xuan, Robert Balkin, Jiequn Han, Ruimeng Hu, Héctor D. Ceniceros:
Optimal Policies for a Pandemic: A Stochastic Game Approach and a Deep Learning Algorithm. CoRR abs/2012.06745 (2020) - 2019
- [i3]Ruimeng Hu:
Deep Learning for Ranking Response Surfaces with Applications to Optimal Stopping Problems. CoRR abs/1901.03478 (2019) - [i2]Ruimeng Hu:
Deep Fictitious Play for Stochastic Differential Games. CoRR abs/1903.09376 (2019) - [i1]Jiequn Han, Ruimeng Hu:
Deep Fictitious Play for Finding Markovian Nash Equilibrium in Multi-Agent Games. CoRR abs/1912.01809 (2019)
Coauthor Index
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