90 citations · 92 across the 2 of their papers we have counts for
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cs.LG2022★ 2 cited
FlowX: Towards Explainable Graph Neural Networks via Message Flows
Shurui Gui, Hao Yuan, Jie Wang +3
We investigate the explainability of graph neural networks (GNNs) as a step toward elucidating their working mechanisms. While most current methods focus on explaining graph nodes,…
cs.LG2021★ 90 cited
On Explainability of Graph Neural Networks via Subgraph Explorations
Hao Yuan, Haiyang Yu, Jie Wang +2
We consider the problem of explaining the predictions of graph neural networks (GNNs), which otherwise are considered as black boxes. Existing methods invariably focus on explainin…