57 citations · 127 across the 8 of their papers we have counts for
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cs.SI2022
Revisiting Adversarial Attacks on Graph Neural Networks for Graph Classification
Xin Wang, Heng Chang, Beini Xie +5
Graph neural networks (GNNs) have achieved tremendous success in the task of graph classification and its diverse downstream real-world applications. Despite the huge success in le…
cs.SI2022★ 37 cited
Semi-Supervised Hierarchical Graph Classification
Jia Li, Yongfeng Huang, Heng Chang +1
Node classification and graph classification are two graph learning problems that predict the class label of a node and the class label of a graph respectively. A node of a graph u…
cs.SI2019★ 5 cited
A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models
Heng Chang, Yu Rong, Tingyang Xu +5
With the great success of graph embedding model on both academic and industry area, the robustness of graph embedding against adversarial attack inevitably becomes a central proble…