Aurora E. Clark

MolSelector: A Machine Learning Framework for Interpretable Subset Selection from Molecular Science Data Sets.

We describe MolSelector, a machine learning framework for selecting representative subsets of molecular science data sets for efficient and accurate neural network training. As part of MolSelector, we introduce the interpretable Atypicality Score algorithm, which identifies molecules that are typical versus atypical of...