3 papers
cs.LG2025
GCL-GCN: Graphormer and Contrastive Learning Enhanced Attributed Graph Clustering Network
Binxiong Li, Xu Xiang, Xue Li +5
Attributed graph clustering holds significant importance in modern data analysis. However, due to the complexity of graph data and the heterogeneity of node attributes, leveraging…
cs.LG2025
Attributed Graph Clustering with Multi-Scale Weight-Based Pairwise Coarsening and Contrastive Learning
Binxiong Li, Yuefei Wang, Binyu Zhao +7
This study introduces the Multi-Scale Weight-Based Pairwise Coarsening and Contrastive Learning (MPCCL) model, a novel approach for attributed graph clustering that effectively bri…
cs.LG2025
Tri-Learn Graph Fusion Network for Attributed Graph Clustering
Binxiong Li, Xu Xiang, Xue Li +3
In recent years, models based on Graph Convolutional Networks (GCN) have made significant strides in the field of graph data analysis. However, challenges such as over-smoothing an…