Lutong Wu

Multi-scale Explainer for Graph Neural Networks

Explainability for graph neural networks (GNNs) aims to unveil the complex decision logic of learned models by identifying the most influential structures in the input graph, thereby improving transparency and trustworthiness. Existing post-hoc explainers typically extract a sparse key subgraph at a…