1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Unsupervised Graph Modeling for Anomaly Detection in Accounting Subject Relationships
Yuhan Wang, Ruobing Yan, Zhe Su +3
This paper addresses the problem of anomaly detection in accounting subject association structures, proposing a structured modeling and unsupervised discriminant framework based on…
cs.LG2025
Towards Automated Self-Supervised Learning for Truly Unsupervised Graph Anomaly Detection
Zhong Li, Yuhang Wang, Matthijs van Leeuwen
Self-supervised learning (SSL) is an emerging paradigm that exploits supervisory signals generated from the data itself, and many recent studies have leveraged SSL to conduct graph…
cs.LG2024★ 1 cited
Explainable Graph Neural Networks Under Fire
Zhong Li, Simon Geisler, Yuhang Wang +2
Predictions made by graph neural networks (GNNs) usually lack interpretability due to their complex computational behavior and the abstract nature of graphs. In an attempt to tackl…