2 papers
cs.LG2026
A Comparative Investigation of Thermodynamic Structure-Informed Neural Networks
Guojie Li, Liu Hong
Physics-informed neural networks (PINNs) offer a unified framework for solving both forward and inverse problems of differential equations, yet their performance and physical consi…
math.DS2026
Incorporating Continuous Dependence Qualifies Physics-Informed Neural Networks for Operator Learning
Guojie Li, Wuyue Yang, Liu Hong
Physics-informed neural networks (PINNs) have been proven as a promising way for solving various partial differential equations, especially high-dimensional ones and those with irr…