3 papers
cs.CV2025
SMART: Semantic Matching Contrastive Learning for Partially View-Aligned Clustering
Liang Peng, Yixuan Ye, Cheng Liu +5
Multi-view clustering has been empirically shown to improve learning performance by leveraging the inherent complementary information across multiple views of data. However, in rea…
cs.SI2025
Trustworthy Neighborhoods Mining: Homophily-Aware Neutral Contrastive Learning for Graph Clustering
Liang Peng, Yixuan Ye, Cheng Liu +4
Recently, neighbor-based contrastive learning has been introduced to effectively exploit neighborhood information for clustering. However, these methods rely on the homophily assum…
cs.AI2025
Refinement Contrastive Learning of Cell-Gene Associations for Unsupervised Cell Type Identification
Liang Peng, Haopeng Liu, Yixuan Ye +4
Unsupervised cell type identification is crucial for uncovering and characterizing heterogeneous populations in single cell omics studies. Although a range of clustering methods ha…