2 citations · 3 across the 9 of their papers we have counts for
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cs.LG2022
Optimal Propagation for Graph Neural Networks
Beidi Zhao, Boxin Du, Zhe Xu +2
Graph Neural Networks (GNNs) have achieved tremendous success in a variety of real-world applications by relying on the fixed graph data as input. However, the initial input graph…
cs.LG2022★ 2 cited
Detecting Topology Attacks against Graph Neural Networks
Senrong Xu, Yuan Yao, Liangyue Li +3
Graph neural networks (GNNs) have been widely used in many real applications, and recent studies have revealed their vulnerabilities against topology attacks. To address this issue…