2 papers
cs.LG2025
Rethinking Contrastive Learning in Graph Anomaly Detection: A Clean-View Perspective
Di Jin, Jingyi Cao, Xiaobao Wang +4
Graph anomaly detection aims to identify unusual patterns in graph-based data, with wide applications in fields such as web security and financial fraud detection. Existing methods…
cs.LG2025
A Survey on Temporal Interaction Graph Representation Learning: Progress, Challenges, and Opportunities
Pengfei Jiao, Hongjiang Chen, Xuan Guo +3
Temporal interaction graphs (TIGs), defined by sequences of timestamped interaction events, have become ubiquitous in real-world applications due to their capability to model compl…