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Optimal Policies for a Pandemic: A Stochastic Game Approach and a Deep
  Learning Algorithm
v1v2 (latest)

Optimal Policies for a Pandemic: A Stochastic Game Approach and a Deep Learning Algorithm

Mathematical and Scientific Machine Learning (MSML), 2020
12 December 2020
Yao Xuan
R. Balkin
Jiequn Han
Ruimeng Hu
Héctor D. Ceniceros
ArXiv (abs)PDFHTML

Papers citing "Optimal Policies for a Pandemic: A Stochastic Game Approach and a Deep Learning Algorithm"

5 / 5 papers shown
Pandemic Control, Game Theory and Machine Learning
Pandemic Control, Game Theory and Machine Learning
Yao Xuan
R. Balkin
Jiequn Han
Ruimeng Hu
Héctor D. Ceniceros
AI4CE
123
2
0
18 Aug 2022
Learning High-Dimensional McKean-Vlasov Forward-Backward Stochastic
  Differential Equations with General Distribution Dependence
Learning High-Dimensional McKean-Vlasov Forward-Backward Stochastic Differential Equations with General Distribution DependenceSIAM Journal on Numerical Analysis (SINUM), 2022
Jiequn Han
Ruimeng Hu
Jihao Long
AI4CEOOD
352
30
0
25 Apr 2022
Signatured Deep Fictitious Play for Mean Field Games with Common Noise
Signatured Deep Fictitious Play for Mean Field Games with Common NoiseInternational Conference on Machine Learning (ICML), 2021
Ming Min
Ruimeng Hu
179
30
0
06 Jun 2021
A Class of Dimension-free Metrics for the Convergence of Empirical
  Measures
A Class of Dimension-free Metrics for the Convergence of Empirical MeasuresStochastic Processes and their Applications (SPA), 2021
Jiequn Han
Ruimeng Hu
Jihao Long
451
4
0
24 Apr 2021
Recurrent Neural Networks for Stochastic Control Problems with Delay
Recurrent Neural Networks for Stochastic Control Problems with DelayMCSS. Mathematics of Control, Signals and Systems (MCSS), 2021
Jiequn Han
Ruimeng Hu
223
22
0
05 Jan 2021
1
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