Statistical Feature Augmentation for Anomaly Detection in Dynamic Graphs
A statistical feature augmentation method that explicitly encodes behavioral interaction statistics into the input feature space and consistently improves detection performance is proposed, showcasing a promising approach for merging classical network analysis with deep learning.
Philipp Schlinge, Jean-Luc Schnipper, M. Atzmueller
· 0 citations