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20222026
most citedFrom Unsupervised to Few-shot Graph Anomaly Detection: A Multi-scale Contrastive Learning Approach

10 citations · 10 across the 7 of their papers we have counts for

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cs.LG2023

PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection

Junjun Pan, Yixin Liu, Yizhen Zheng +1

Node-level graph anomaly detection (GAD) plays a critical role in identifying anomalous nodes from graph-structured data in various domains such as medicine, social networks, and e…