2026
Topological Anomaly Quantification for Semi-supervised Graph Anomaly Detection
ICLR 2026poster
Semi-supervised graph anomaly detection identifies nodes deviating from normal patterns using a limited set of labeled nodes. This paper specifically addresses the challenging scenario where only normal node labels are available. To address the challenge of anomaly scarcity in real-world graphs, gen…