AI RESEARCH
A Comparative Investigation of Thermodynamic Structure-Informed Neural Networks
arXiv CS.LG
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ArXi:2603.26803v1 Announce Type: new 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 on how governing laws are incorporated.