Sparse Fusion

Sparse Fusion is a multi-omics data integration method that belongs to the class of fusion techniques leveraging sparsity-inducing constraints to selectively prioritize informative features or samples, thereby distinguishing itself through the explicit modeling of data sparsity to enhance interpretability and reduce overfitting in high-dimensional biological datasets.

21

Publications

788

Citations

90

Authors

49

Institutions

Publications per year

2017–2026

10

Authors

90

  1. RB
    Richard Bamler

    Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR), Germany

    3 publications · 198 citations

    3

    h-index

  2. XX
    Xiao Xiang Zhu

    Technical University of Munich, Germany

    3 publications · 198 citations

    3

    h-index

  3. CG
    Claas Grohnfeldt

    Technical University of Munich, Germany

    2 publications · 187 citations

    2

    h-index

  4. WH
    Wen Hu

    UNSW Sydney, Australia

    1 publications · 55 citations

    1

    h-index

  5. YZ
    Ying Zhu

    Siemens (United States), United States

    1 publications · 15 citations

    1

    h-index

1–5 of 90

Venues

  1. 2

    h-index

  2. Biomedical Signal Processing and Control

    1 publications · 22 citations

    1

    h-index

  3. PLoS ONE

    1 publications · 10 citations

    1

    h-index

  4. 1

    h-index

  5. 1

    h-index

1–5