Comparative Analysis of Single-Generator and Double-Generator Formalisms for Thermodynamics-Informed Neural Networks

The core message of this paper is to analyze the advantages and disadvantages of using single-generator and double-generator (GENERIC) formalisms to incorporate thermodynamic principles into neural network models for predicting physical phenomena.