Performance Increases in Physics-Informed Machine Learning using Hypercomplex-based Automatic Differentiation (HYPAD)
Physics-Informed Machine Learning (PIML) integrates physical laws into neural network training to solve complex problems governed by differential equations. A critical component in PIML is computing derivatives of models to ensure compliance with the governing equations. A common approach is to use automatic differenti...