Tag
The paper introduces a three-stage training pipeline using procedural pretraining to improve molecular property prediction, showing enhanced performance under data scarcity by learning inductive biases from abstract generated data.
GraphNOSE is an open-source graph transformer framework that predicts multi-label odor descriptors from molecular structures, achieving superior performance over existing methods with fewer parameters and improved generalization to out-of-distribution compounds.