1 citations · 1 across the 8 of their papers we have counts for
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AHSG: Adversarial Attack on High-level Semantics in Graph Neural Networks
Kai Yuan, Jiahao Zhang, Yidi Wang +1
Adversarial attacks on Graph Neural Networks aim to perturb the performance of the learner by carefully modifying the graph topology and node attributes. Existing methods achieve a…
IENE: Identifying and Extrapolating the Node Environment for Out-of-Distribution Generalization on Graphs
Haoran Yang, Xiaobing Pei, Kai Yuan
Due to the performance degradation of graph neural networks (GNNs) under distribution shifts, the work on out-of-distribution (OOD) generalization on graphs has received widespread…
Hyperedge Interaction-aware Hypergraph Neural Network
Rongping Ye, Xiaobing Pei, Haoran Yang +1
Hypergraphs provide an effective modeling approach for modeling high-order relationships in many real-world datasets. To capture such complex relationships, several hypergraph neur…
Semi-supervised learning via DQN for log anomaly detection
Yingying He, Xiaobing Pei
Log anomaly detection is a critical component in modern software system security and maintenance, serving as a crucial support and basis for system monitoring, operation, and troub…