18 citations · 28 across the 4 of their papers we have counts for
4 papers
Clustering-Oriented Generative Attribute Graph Imputation
Mulin Chen, Bocheng Wang, Jiaxin Zhong +2
Attribute-missing graph clustering has emerged as a significant unsupervised task, where only attribute vectors of partial nodes are available and the graph structure is intact. Th…
Towards Learnable Anchor for Deep Multi-View Clustering
Bocheng Wang, Chusheng Zeng, Mulin Chen +1
Deep multi-view clustering incorporating graph learning has presented tremendous potential. Most methods encounter costly square time consumption w.r.t. data size. Theoretically, a…
Multi-Task Curriculum Graph Contrastive Learning with Clustering Entropy Guidance
Chusheng Zeng, Bocheng Wang, Jinghui Yuan +2
Recent advances in unsupervised deep graph clustering have been significantly promoted by contrastive learning. Despite the strides, most graph contrastive learning models face cha…
Deep Contrastive Graph Learning with Clustering-Oriented Guidance
Mulin Chen, Bocheng Wang, Xuelong Li
Graph Convolutional Network (GCN) has exhibited remarkable potential in improving graph-based clustering. To handle the general clustering scenario without a prior graph, these mod…