Ryan Henderson

Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity

Rationalizing which parts of a molecule drive the predictions of a molecular graph convolutional neural network (GCNN) can be difficult. To help, we propose two simple regularization techniques to apply during the training of GCNNs: Batch Representation Orthonormalization (BRO) and Gini regularizati…