IEEE transactions on pattern analysis and machine intelligence
MoEGAD: A Mixture-of-Experts Framework with Pseudo-Anomaly Generation for Graph-Level Anomaly Detection.
Jinyu Cai, Yunhe Zhang, Pengyang Wang, See-Kiong Ng
Published: 202510.1109/TPAMI.2025.3646069
Abstract
Graph-level anomaly detection (GLAD) aims to identify graphs that significantly deviate from the norm. Despite remarkable advancements in recent years, existing GLAD approaches struggle with the scarcity of labeled anomalies. Although some semi-super…
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