A variational-inference explainer that uses a Beta-distributed edge mask to identify important edges in graph neural networks, with uncertainty scores, evaluated on simulated graphs.
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BetaExplainer: A Probabilistic Method to Explain Graph Neural Networks
A variational-inference explainer that uses a Beta-distributed edge mask to identify important edges in graph neural networks, with uncertainty scores, evaluated on simulated graphs.