22557e7132
- 7-8월 초기 구축 문서 12개를 _archive/troubleshooting/2025_07-08_initial_setup/로 이동 - book/300_architecture/390_human_in_the_loop_intent_learning.md를 journey/research/intent_classification/로 이동 (개발 여정 문서) - 빈 폴더 제거 (journey/assets/*)
558 B
558 B
GNNExplainer: Generating Explanations for Graph Neural Networks
- Authors: Rex Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, Jure Leskovec
- Year: 2019
- Summary: This paper introduces GNNExplainer, a method for explaining the predictions of Graph Neural Networks (GNNs). It identifies a compact subgraph and a small subset of node features that are most influential for a given prediction. This is crucial for understanding GNN decisions in domains like social networks or knowledge graphs.
- Link: https://arxiv.org/abs/1903.03894