Mitigating Homophily Disparity in Graph Anomaly Detection: A Scalable and Adaptive Approach
Mitigating Homophily Disparity in Graph Anomaly Detection: A Scalable and Adaptive Approach explores SAGAD is a scalable graph anomaly detection framework that adaptively fuses low- and high-frequency information to identify anomalous nodes in large-scale graphs, offering superior accuracy and scalability.. Commercial viability score: 7/10 in Graph Anomaly Detection.
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