7 citations · 9 across the 9 of their papers we have counts for
4 papers · 1 filter
Graph Anomaly Detection at Group Level: A Topology Pattern Enhanced Unsupervised Approach
Xing Ai, Jialong Zhou, Yulin Zhu +4
Graph anomaly detection (GAD) has achieved success and has been widely applied in various domains, such as fraud detection, cybersecurity, finance security, and biochemistry. Howev…
Robust Graph Contrastive Learning with Information Restoration
Yulin Zhu, Xing Ai, Yevgeniy Vorobeychik +1
The graph contrastive learning (GCL) framework has gained remarkable achievements in graph representation learning. However, similar to graph neural networks (GNNs), GCL models are…
Labeled Subgraph Entropy Kernel
Chengyu Sun, Xing Ai, Zhihong Zhang +1
In recent years, kernel methods are widespread in tasks of similarity measuring. Specifically, graph kernels are widely used in fields of bioinformatics, chemistry and financial da…
Simple yet Effective Gradient-Free Graph Convolutional Networks
Yulin Zhu, Xing Ai, Qimai Li +2
Linearized Graph Neural Networks (GNNs) have attracted great attention in recent years for graph representation learning. Compared with nonlinear Graph Neural Network (GNN) models,…