4 citations · 26 across the 21 of their papers we have counts for
5 papers · 1 filter
Graph Neural Networks for Brain Graph Learning: A Survey
Xuexiong Luo, Jia Wu, Jian Yang +7
Exploring the complex structure of the human brain is crucial for understanding its functionality and diagnosing brain disorders. Thanks to advancements in neuroimaging technology,…
FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing
Yongzhe Jia, Xuyun Zhang, Amin Beheshti +1
Federated Learning (FL) has emerged as a promising solution in Edge Computing (EC) environments to process the proliferation of data generated by edge devices. By collaboratively o…
OptIForest: Optimal Isolation Forest for Anomaly Detection
Haolong Xiang, Xuyun Zhang, Hongsheng Hu +5
Anomaly detection plays an increasingly important role in various fields for critical tasks such as intrusion detection in cybersecurity, financial risk detection, and human health…
A Comprehensive Survey on Graph Summarization with Graph Neural Networks
Nasrin Shabani, Jia Wu, Amin Beheshti +5
As large-scale graphs become more widespread, more and more computational challenges with extracting, processing, and interpreting large graph data are being exposed. It is therefo…
DAGAD: Data Augmentation for Graph Anomaly Detection
Fanzhen Liu, Xiaoxiao Ma, Jia Wu +7
Graph anomaly detection in this paper aims to distinguish abnormal nodes that behave differently from the benign ones accounting for the majority of graph-structured instances. Rec…