26 citations · 59 across the 9 of their papers we have counts for
4 papers · 1 filter
Chasing Label Shifters: A Change-Aware Framework for Dynamic Graph Node Classification
Junghoon Kim, Seungyoon Choi, Hyunsung Kim +1
Entities in real-world systems often evolve over time: users shift between information consumption patterns, researchers migrate between fields, and firms transition between financ…
Toward Reasoning on the Boundary: A Mixup-based Approach for Graph Anomaly Detection
Hwan Kim, Junghoon Kim, Sungsu Lim
While GNN-based detection methods excel at identifying overt outliers, they often struggle with boundary anomalies -- subtly camouflaged nodes that are difficult to distinguish fro…
Class Label-aware Graph Anomaly Detection
Junghoon Kim, Yeonjun In, Kanghoon Yoon +2
Unsupervised GAD methods assume the lack of anomaly labels, i.e., whether a node is anomalous or not. One common observation we made from previous unsupervised methods is that they…
Label-based Graph Augmentation with Metapath for Graph Anomaly Detection
Hwan Kim, Junghoon Kim, Byung Suk Lee +1
Graph anomaly detection has attracted considerable attention from various domain ranging from network security to finance in recent years. Due to the fact that labeling is very cos…