OnsagerNet: Learning Stable and Interpretable Dynamics using a Generalized Onsager Principle

6 September 2020

Papers citing "OnsagerNet: Learning Stable and Interpretable Dynamics using a Generalized Onsager Principle"

7 / 7 papers shown

Title
VPNets: Volume-preserving neural networks for learning source-free dynamics Aiqing Zhu Beibei Zhu Jiawei Zhang Yifa Tang Jian-Dong Liu 28 3 0 29 Apr 2022
Computing the Invariant Distribution of Randomly Perturbed Dynamical Systems Using Deep Learning Bo Lin Qianxiao Li W. Ren 16 8 0 22 Oct 2021
Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling Kookjin Lee Nathaniel Trask P. Stinis 32 24 0 11 Sep 2021
A Data Driven Method for Computing Quasipotentials Bo Lin Qianxiao Li W. Ren 11 13 0 13 Dec 2020
Learning Thermodynamically Stable and Galilean Invariant Partial Differential Equations for Non-equilibrium Flows Juntao Huang Zhiting Ma Y. Zhou W. Yong AI4CE 30 16 0 28 Sep 2020
Discovery of Governing Equations with Recursive Deep Neural Networks Jia Zhao Jarrod Mau PINN 17 6 0 24 Sep 2020
Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems Alexander Wikner Jaideep Pathak Brian Hunt M. Girvan T. Arcomano I. Szunyogh Andrew Pomerance Edward Ott AI4CE 62 70 0 10 Feb 2020