Learning Discriminative and Generalizable Anomaly Detector for Dynamic Graph with Limited Supervision

Yuxing Tian, Yiyan Qi, Fengran Mo +3

Dynamic graph anomaly detection is critical for many real-world applications but remains challenging due to the scarcity of labeled anomalies. Existing methods are either unsupervi…