2022
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
AISTATS 2022poster
Given the increasing promise of graph neural networks (GNNs) in real-world applications, several methods have been developed for explaining their predictions. Existing methods for interpreting predictions from GNNs have primarily focused on generating subgraphs that are especially relevant for a par…