6 citations · 10 across the 2 of their papers we have counts for
3 papers
cs.CV2026
Multi-view Graph Convolutional Network with Fully Leveraging Consistency via Granular-ball-based Topology Construction, Feature Enhancement and Interactive Fusion
Chengjie Cui, Taihua Xu, Shuyin Xia +3
The effective utilization of consistency is crucial for multi-view learning. GCNs leverage node connections to propagate information across the graph, facilitating the exploitation…
cs.LG2021★ 4 cited
Graph-Fraudster: Adversarial Attacks on Graph Neural Network Based Vertical Federated Learning
Jinyin Chen, Guohan Huang, Haibin Zheng +3
Graph neural network (GNN) has achieved great success on graph representation learning. Challenged by large scale private data collected from user-side, GNN may not be able to refl…
cs.LG2021★ 6 cited
GraphAttacker: A General Multi-Task GraphAttack Framework
Jinyin Chen, Dunjie Zhang, Zhaoyan Ming +3
Graph neural networks (GNNs) have been successfully exploited in graph analysis tasks in many real-world applications. The competition between attack and defense methods also enhan…