472 citations · 621 across the 23 of their papers we have counts for
5 papers · 1 filter
Graph Transformers: A Survey
Ahsan Shehzad, Feng Xia, Shagufta Abid +4
Graph transformers are a recent advancement in machine learning, offering a new class of neural network models for graph-structured data. The synergy between transformers and graph…
Collaborative Team Recognition: A Core Plus Extension Structure
Shuo Yu, Fayez Alqahtani, Amr Tolba +3
Scientific collaboration is a significant behavior in knowledge creation and idea exchange. To tackle large and complex research questions, a trend of team formation has been obser…
Higher-order Structure Based Anomaly Detection on Attributed Networks
Xu Yuan, Na Zhou, Shuo Yu +3
Anomaly detection (such as telecom fraud detection and medical image detection) has attracted the increasing attention of people. The complex interaction between multiple entities…
FUGNN: Harmonizing Fairness and Utility in Graph Neural Networks
Renqiang Luo, Huafei Huang, Shuo Yu +4
Fairness-aware Graph Neural Networks (GNNs) often face a challenging trade-off, where prioritizing fairness may require compromising utility. In this work, we re-examine fairness t…
FairGT: A Fairness-aware Graph Transformer
Renqiang Luo, Huafei Huang, Shuo Yu +2
The design of Graph Transformers (GTs) generally neglects considerations for fairness, resulting in biased outcomes against certain sensitive subgroups. Since GTs encode graph info…