PotentialNet for Molecular Property Prediction

, to measure the early enrichment of computational models for chemical data. Finally, we introduce a cross-validation strategy based on structural homology clustering that can more accurately measure model generalizability, which crucially distinguishes the aims of machine learning for drug discovery from standard machine learning tasks.

PotentialNet for Molecular Property Prediction | Litlas