Search Results for author:
Found 2 papers, 1 papers with code
Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive Learning
Finally, the model is refined with the only input of reliable normal nodes and learns a more accurate estimate of normality so that anomalous nodes can be more easily distinguished.
ARISE: Graph Anomaly Detection on Attributed Networks via Substructure Awareness
The average node-pair similarity can be regarded as the topology anomaly degree of nodes within substructures.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
