Christian Natajaya

Causal-Chemprop: Causal Machine Learning for Molecular Property Prediction and Design

A priori estimation of molecular properties has long been a topic of immense interest to the pharmaceutical sciences for molecular design. While neural network-based models have achieved high predictive accuracy, they have limited utility in molecular design, particularly in small and out-of-distribution data regimes...