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cs.LG2025
GTHNA: Local-global Graph Transformer with Memory Reconstruction for Holistic Node Anomaly Evaluation
Mingkang Li, Xuexiong Luo, Yue Zhang +2
Anomaly detection in graph-structured data is an inherently challenging problem, as it requires the identification of rare nodes that deviate from the majority in both their struct…
cs.LG2023★ 2 cited
Multi-representations Space Separation based Graph-level Anomaly-aware Detection
Fu Lin, Haonan Gong, Mingkang Li +3
Graph structure patterns are widely used to model different area data recently. How to detect anomalous graph information on these graph data has become a popular research problem.…