46 citations · 63 across the 10 of their papers we have counts for
3 papers · 1 filter
Simple and Efficient Partial Graph Adversarial Attack: A New Perspective
Guanghui Zhu, Mengyu Chen, Chunfeng Yuan +1
As the study of graph neural networks becomes more intensive and comprehensive, their robustness and security have received great research interest. The existing global attack meth…
HAGNN: Hybrid Aggregation for Heterogeneous Graph Neural Networks
Guanghui Zhu, Zhennan Zhu, Hongyang Chen +2
Heterogeneous graph neural networks (GNNs) have been successful in handling heterogeneous graphs. In existing heterogeneous GNNs, meta-path plays an essential role. However, recent…
AutoAC: Towards Automated Attribute Completion for Heterogeneous Graph Neural Network
Guanghui Zhu, Zhennan Zhu, Wenjie Wang +3
Many real-world data can be modeled as heterogeneous graphs that contain multiple types of nodes and edges. Meanwhile, due to excellent performance, heterogeneous graph neural netw…