Edge-Level Explanations for Graph Neural Networks by Extending Explainability Methods for Convolutional Neural Networks

Tetsu Kasanishi, Xueting Wang, Toshihiko Yamasaki

Graph Neural Networks (GNNs) are deep learning models that take graph data as inputs, and they are applied to various tasks such as traffic prediction and molecular property predic…