Xihe Xie

Exploring Domain Generalization and Subpopulation Shift for Generalizable Graph-Level Anomaly Detection

Graph-level anomaly detection (GLAD), which identifies rare or atypical graphs within a graph set, is crucial for applications such as image analysis, industrial defect inspection and fraud detection. However, existing GLAD approaches typically rely on the in-distribution hypothesis while lacking ge