Global explanations for Graph Neural Networks

What is it about?

Graph neural networks are powerful but hard to interpret. Existing explanation tools focus only on individual cases, which makes them overwhelming and less useful for broad understanding. We introduce GCFExplainer, a method that creates a small set of global, easy-to-understand explanations. This approach helps uncover how models behave overall, offers clearer guidance, and is more efficient and robust than current alternatives.

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