52 citations · 102 across the 5 of their papers we have counts for
5 papers
EGRC-Net: Embedding-induced Graph Refinement Clustering Network
Zhihao Peng, Hui Liu, Yuheng Jia +1
Existing graph clustering networks heavily rely on a predefined yet fixed graph, which can lead to failures when the initial graph fails to accurately capture the data topology str…
Deep Attention-guided Graph Clustering with Dual Self-supervision
Zhihao Peng, Hui Liu, Yuheng Jia +1
Existing deep embedding clustering works only consider the deepest layer to learn a feature embedding and thus fail to well utilize the available discriminative information from cl…
Adaptive Attribute and Structure Subspace Clustering Network
Zhihao Peng, Hui Liu, Yuheng Jia +1
Deep self-expressiveness-based subspace clustering methods have demonstrated effectiveness. However, existing works only consider the attribute information to conduct the self-expr…
Attention-driven Graph Clustering Network
Zhihao Peng, Hui Liu, Yuheng Jia +1
The combination of the traditional convolutional network (i.e., an auto-encoder) and the graph convolutional network has attracted much attention in clustering, in which the auto-e…
Maximum Entropy Subspace Clustering Network
Zhihao Peng, Yuheng Jia, Hui Liu +2
Deep subspace clustering networks have attracted much attention in subspace clustering, in which an auto-encoder non-linearly maps the input data into a latent space, and a fully c…