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

Last update: Aug 24, 2022

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Deep Learning OnsagerNet

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:

Learning deterministic Langevin dynamics
Learning chaotic and non-chaotic Lorenz63 system
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

[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

GitHub Repository

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

Related tags

Overview

OnsagerNet

Reference

Owner

Haijun.Yu

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