2 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.LG2024★ 2 cited
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…
cs.LG2023
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…
cs.LG2023★ 1 cited
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…