Multi-modal Clustering

Multi-Modal Clustering is a clustering framework that integrates and analyzes multiple distinct but complementary data modalities to jointly identify underlying cellular subpopulations, distinguishing itself from unimodal approaches by leveraging cross-modal consistencies and dependencies for improved biological interpretability and resolution.

69

Publications

3.7K

Citations

247

Authors

131

Institutions

Publications per year

2017–2026

41

Authors

247

  1. DE
    Davide Eynard

    Università della Svizzera italiana, Switzerland

    2 publications · 90 citations

    2

    h-index

  2. WX
    Wei Xia

    Xidian University, China

    2 publications · 78 citations

    2

    h-index

  3. QG
    Quanxue Gao

    Xidian University, China

    2 publications · 78 citations

    2

    h-index

  4. MM
    Michael M. Bronstein

    Università della Svizzera italiana, Switzerland

    2 publications · 90 citations

    2

    h-index

  5. YY
    Yangdong Ye

    Zhengzhou University, China

    2 publications · 70 citations

    2

    h-index

1–5 of 247

Venues

  1. IEEE Transactions on Image Processing

    2 publications · 104 citations

    3

    h-index

  2. 3

    h-index

  3. Advances in Data Analysis and Classification

    3 publications · 65 citations

    3

    h-index

  4. Scientific Reports

    2 publications · 40 citations

    2

    h-index

  5. Multimedia Tools and Applications

    2 publications · 27 citations

    2

    h-index

1–5