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Generative Ensemble Regression: Learning Particle Dynamics from
  Observations of Ensembles with Physics-Informed Deep Generative Models

Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-Informed Deep Generative Models

5 August 2020
Liu Yang
C. Daskalakis
George Karniadakis
ArXivPDFHTML

Papers citing "Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-Informed Deep Generative Models"

2 / 2 papers shown
Title
Extracting Stochastic Governing Laws by Nonlocal Kramers-Moyal Formulas
Extracting Stochastic Governing Laws by Nonlocal Kramers-Moyal Formulas
Yubin Lu
Yang Li
Jinqiao Duan
21
16
0
28 Aug 2021
Solving Inverse Stochastic Problems from Discrete Particle Observations
  Using the Fokker-Planck Equation and Physics-informed Neural Networks
Solving Inverse Stochastic Problems from Discrete Particle Observations Using the Fokker-Planck Equation and Physics-informed Neural Networks
Xiaoli Chen
Liu Yang
Jinqiao Duan
George Karniadakis
16
81
0
24 Aug 2020
1