GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction. (arXiv:2306.01951v4 [cs.LG] UPDATED)

Graph Anomaly Detection (GAD) is a technique used to identify abnormal nodes
within graphs, finding applications in network security, fraud detection,
social media spam detection, and various other domains. A common method for GAD
is Graph Auto-Encoders (GAEs), which encode graph data into node
representations and identify anomalies by assessing the reconstruction quality
of the graphs based on these representations. However, existing GAE models are
primarily optimized for direct link reconstruction, resulting in nodes
connected in the graph being clustered …

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