2 citations · 4 across the 3 of their papers we have counts for
4 papers
GLADformer: A Mixed Perspective for Graph-level Anomaly Detection
Fan Xu, Nan Wang, Hao Wu +7
Graph-Level Anomaly Detection (GLAD) aims to distinguish anomalous graphs within a graph dataset. However, current methods are constrained by their receptive fields, struggling to…
LTRDetector: Exploring Long-Term Relationship for Advanced Persistent Threats Detection
Xiaoxiao Liu, Fan Xu, Nan Wang +4
Advanced Persistent Threat (APT) is challenging to detect due to prolonged duration, infrequent occurrence, and adept concealment techniques. Existing approaches primarily concentr…
Revisiting Graph-Based Fraud Detection in Sight of Heterophily and Spectrum
Fan Xu, Nan Wang, Hao Wu +3
Graph-based fraud detection (GFD) can be regarded as a challenging semi-supervised node binary classification task. In recent years, Graph Neural Networks (GNN) have been widely ap…
Few-shot Message-Enhanced Contrastive Learning for Graph Anomaly Detection
Fan Xu, Nan Wang, Xuezhi Wen +3
Graph anomaly detection plays a crucial role in identifying exceptional instances in graph data that deviate significantly from the majority. It has gained substantial attention in…