cs.LG, stat.ML

A Comparative Investigation of Thermodynamic Structure-Informed Neural Networks

arXiv:2603.26803v1 Announce Type: new
Abstract: Physics-informed neural networks (PINNs) offer a unified framework for solving both forward and inverse problems of differential equations, yet their performance and physical consistency strongly depend …