DeNoise: Learning Robust Graph Representations for Unsupervised Graph-Level Anomaly Detection

Qingfeng Chen, Haojin Zeng, Jingyi Jie +2

With the rapid growth of graph-structured data in critical domains, unsupervised graph-level anomaly detection (UGAD) has become a pivotal task. UGAD seeks to identify entire graph…