Summary
International Symposium on Nonlinear Theory and Its Applications
2022
Session Number:A2L-D
Session:
Number:A2L-D-03
Learning Generic Systems Using Neural Symplectic Forms
Baige Xu , Yuhan Chen , Takashi Matsubara , Takaharu Yaguchi,
pp.29-32
Publication Date:12/12/2022
Online ISSN:2188-5079
Summary:
The GENERIC formulation is a way of describing non-equilibrium thermodynamic systems, and GENERIC systems are systems formulated as such. For learning such systems from data, GFINN is an existing method. In this talk, we improved it by applying the recently proposed neural symplectic form, so that it becomes possible to model general GENERIC systems on general symplectic manifolds using data represented by general coordinate systems.