Interpretable machine learning in Physics
arXiv:2203.08021 · doi:10.1038/s42254-022-00456-0
Abstract
Adding interpretability to multivariate methods creates a powerful synergy for exploring complex physical systems with higher order correlations while bringing about a degree of clarity in the underlying dynamics of the system.
Submitted version of invited Comment Article for Nature Reviews Physics (2022)