Sequential Design for Ranking Response Surfaces. - Ruimeng Hu; Mike Ludkovski (SIAM/ASA J. Uncertain. Quantification, 2017)

Asymptotic Optimal Strategy for Portfolio Optimization in a Slowly Varying Stochastic Environment. - Jean-Pierre Fouque; Ruimeng Hu (SIAM J. Control. Optim., 2017)

Asymptotic Optimal Portfolio in Fast Mean-Reverting Stochastic Environments. - Ruimeng Hu (CDC, 2018)

Systemic risk and optimal fee for central clearing counterparty under partial netting. - Zhenyu Cui; Qi Feng 002; Ruimeng Hu; Bin Zou 005 (Oper. Res. Lett., 2018)

Optimal Portfolio under Fast Mean-Reverting Fractional Stochastic Environment. - Jean-Pierre Fouque; Ruimeng Hu (SIAM J. Financial Math., 2018)

Deep Learning for Ranking Response Surfaces with Applications to Optimal Stopping Problems. - Ruimeng Hu (CoRR, 2019)

Deep Fictitious Play for Stochastic Differential Games. - Ruimeng Hu (CoRR, 2019)

Deep Fictitious Play for Finding Markovian Nash Equilibrium in Multi-Agent Games. - Jiequn Han; Ruimeng Hu (MSML, 2020)

Convergence of Deep Fictitious Play for Stochastic Differential Games. - Jiequn Han; Ruimeng Hu; Jihao Long (CoRR, 2020)

Multiscale Asymptotic Analysis for Portfolio Optimization under Stochastic Environment. - Jean-Pierre Fouque; Ruimeng Hu (Multiscale Model. Simul., 2020)

Signatured Deep Fictitious Play for Mean Field Games with Common Noise. - Ming Min; Ruimeng Hu (ICML, 2021)

Optimal Policies for a Pandemic: A Stochastic Game Approach and a Deep Learning Algorithm. - Yao Xuan; Robert Balkin; Jiequn Han; Ruimeng Hu; Héctor D. Ceniceros (MSML, 2021)

A Class of Dimensionality-free Metrics for the Convergence of Empirical Measures. - Jiequn Han; Ruimeng Hu; Jihao Long (CoRR, 2021)

Recurrent neural networks for stochastic control problems with delay. - Jiequn Han; Ruimeng Hu (Math. Control. Signals Syst., 2021)

Pandemic Control, Game Theory and Machine Learning. - Yao Xuan; Robert Balkin; Jiequn Han; Ruimeng Hu; Héctor D. Ceniceros (CoRR, 2022)

Higher-Order Error estimates for physics-informed neural networks approximating the primitive equations. - Ruimeng Hu; Quyuan Lin; Alan Raydan; Sui Tang (CoRR, 2022)

Sub- and Supersolution Approach to Accuracy Analysis of Portfolio Optimization Asymptotics in Multiscale Stochastic Factor Markets. - Jean-Pierre Fouque; Ruimeng Hu; Ronnie Sircar (SIAM J. Financial Math., 2022)

Directed Chain Generative Adversarial Networks. - Ming Min; Ruimeng Hu; Tomoyuki Ichiba (ICML, 2023)

Recent Developments in Machine Learning Methods for Stochastic Control and Games. - Ruimeng Hu; Mathieu Laurière (CoRR, 2023)

Stochastic Delay Differential Games: Financial Modeling and Machine Learning Algorithms. - Robert Balkin; Héctor D. Ceniceros; Ruimeng Hu (CoRR, 2023)

Deep Reinforcement Learning for Infinite Horizon Mean Field Problems in Continuous Spaces. - Andrea Angiuli; Jean-Pierre Fouque; Ruimeng Hu; Alan Raydan (CoRR, 2023)

A Deep Learning Analysis of Climate Change, Innovation, and Uncertainty. - Michael Barnett; William Brock; Lars Peter Hansen; Ruimeng Hu; Joseph Huang (CoRR, 2023)

Convergence of the Backward Deep BSDE Method with Applications to Optimal Stopping Problems. - Chengfan Gao; Siping Gao; Ruimeng Hu; Zimu Zhu (SIAM J. Financial Math., 2023)

Accuracy Analysis of Physics-Informed Neural Networks for Approximating the Critical SQG Equation. - Elie Abdo; Ruimeng Hu; Quyuan Lin (CoRR, 2024)

Error estimates of physics-informed neural networks for approximating Boltzmann equation. - Elie Abdo; Lihui Chai; Ruimeng Hu; Xu Yang 018 (CoRR, 2024)

Learning High-Dimensional McKean-Vlasov Forward-Backward Stochastic Differential Equations with General Distribution Dependence. - Jiequn Han; Ruimeng Hu; Jihao Long (SIAM J. Numer. Anal., 2024)

Multiagent Relative Investment Games in a Jump Diffusion Market with Deep Reinforcement Learning Algorithm. - Liwei Lu; Ruimeng Hu; Xu Yang 018; Yi Zhu 010 (SIAM J. Financial Math., 2025)

Regularization by Noise for the Inviscid Primitive Equations. - Ruimeng Hu; Quyuan Lin; Rongchang Liu (J. Nonlinear Sci., 2025)

Finite-Agent Stochastic Differential Games on Large Graphs: II. Graph-Based Architectures. - Ruimeng Hu; Jihao Long; Haosheng Zhou (CoRR, 2025)

Learning Mean-Field Games through Mean-Field Actor-Critic Flow. - Mo Zhou; Haosheng Zhou; Ruimeng Hu (CoRR, 2025)