Learning hidden low dimensional dyanmics using a Generalized Onsager Principle and neural networks

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Deep LearningOnsagerNet
Overview

OnsagerNet

Learning hidden low dimensional dyanmics using a Generalized Onsager Principle and neural networks

This is the original pyTorch implemenation of OnsagerNet with three applications:

  1. Learning deterministic Langevin dynamics
  2. Learning chaotic and non-chaotic Lorenz63 system
  3. Learning a reduced model for Rayleigh Bernard Convection (RBC) based only on trajectory data.

See the ReadMe.md in each subfolder and the reference paper for more information.

Reference

  1. [PhyRevF] H. Yu, X. Tian, W. E and Q. Li, OnsagerNet: Learning Stable and Interpretable Dynamics using a Generalized Onsager Principle, arxiv:2009.02327, to appear on Physical Review Fluids, 2021.
Owner
Haijun.Yu
Haijun.Yu
GitHub Repository
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