Umap Visualization

Umap Visualization is a dimensionality reduction technique that preserves both local and global data structures by constructing a topological representation of high-dimensional data through probabilistic modeling and graph layout optimization.

5

Publications

5.9K

Citations

17

Authors

9

Institutions

Publications per year

2017–2026

5

Authors

17

  1. JL
    Jiesi Luo

    Sichuan University, China

    1 publications · 16 citations

    1

    h-index

  2. EW
    Evan W. Newell

    Singapore Immunology Network, Singapore

    1 publications · 5.8K citations

    1

    h-index

  3. JH
    John Healy

    Ernst Strüngmann Institute for Neuroscience, Germany

    1 publications · 5.8K citations

    1

    h-index

  4. LG
    Lai Guan Ng

    Singapore Immunology Network, Singapore

    1 publications · 5.8K citations

    1

    h-index

  5. VM
    Vivien Marx

    The Nature Conservancy, United States

    1 publications · 58 citations

    1

    h-index

1–5 of 17

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 42 citations

    2

    h-index

  2. iScience

    1 publications · 16 citations

    1

    h-index

  3. Nature Methods

    1 publications · 58 citations

    1

    h-index

  4. Nature Biotechnology

    1 publications · 5.8K citations

    1

    h-index

  5. Neural Networks

    1 publications · 15 citations

1–5