Model-free quantification of completeness, uncertainties, and outliers in atomistic machine learning using information theory

Daniel Schwalbe-Koda, Sebastien Hamel, Babak Sadigh +2

An accurate description of information is relevant for a range of problems in atomistic machine learning (ML), such as crafting training sets, performing uncertainty quantification…