17 citations · 22 across the 9 of their papers we have counts for
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cs.LG2024★ 1 cited
Generating Robust Counterfactual Witnesses for Graph Neural Networks
Dazhuo Qiu, Mengying Wang, Arijit Khan +1
This paper introduces a new class of explanation structures, called robust counterfactual witnesses (RCWs), to provide robust, both counterfactual and factual explanations for grap…
cs.LG2024★ 17 cited
View-based Explanations for Graph Neural Networks
Tingyang Chen, Dazhuo Qiu, Yinghui Wu +3
Generating explanations for graph neural networks (GNNs) has been studied to understand their behavior in analytical tasks such as graph classification. Existing approaches aim to…