21 citations · 30 across the 2 of their papers we have counts for
4 papers
Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View
Jingcan Duan, Siwei Wang, Pei Zhang +5
Graph anomaly detection (GAD) is a vital task in graph-based machine learning and has been widely applied in many real-world applications. The primary goal of GAD is to capture ano…
Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems
Massimiliano Lupo Pasini, Pei Zhang, Samuel Temple Reeve +1
We introduce a multi-tasking graph convolutional neural network, HydraGNN, to simultaneously predict both global and atomic physical properties and demonstrate with ferromagnetic m…
Multi-view Clustering via Deep Matrix Factorization and Partition Alignment
Chen Zhang, Siwei Wang, Jiyuan Liu +5
Multi-view clustering (MVC) has been extensively studied to collect multiple source information in recent years. One typical type of MVC methods is based on matrix factorization to…
Multi-view Clustering with Deep Matrix Factorization and Global Graph Refinement
Chen Zhang, Siwei Wang, Wenxuan Tu +4
Multi-view clustering is an important yet challenging task in machine learning and data mining community. One popular strategy for multi-view clustering is matrix factorization whi…