Sampling-based Visualization

Sampling-Based Visualization is a visualization approach that employs statistical sampling techniques to generate representative subsets of data for visual representation, thereby enabling efficient exploration and analysis of large and complex datasets while preserving underlying structural properties.

30

Publications

1.3K

Citations

90

Authors

40

Institutions

Publications per year

2017–2026

11

Authors

90

  1. EB
    Enrico Bertini

    New York University, United States

    3 publications · 114 citations

    3

    h-index

  2. AD
    Alan Dix

    Lancaster University, United Kingdom

    3 publications · 133 citations

    3

    h-index

  3. GS
    Giuseppe Santucci

    Sapienza University of Rome, Italy

    3 publications · 114 citations

    3

    h-index

  4. GE
    G. Ellis

    Centre National de la Recherche Scientifique, France

    2 publications · 102 citations

    2

    h-index

  5. EB
    Eric Blais

    Carnegie Mellon University, United States

    2 publications · 171 citations

    2

    h-index

1–5 of 90

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 4 publications · 221 citations

    4

    h-index

  2. Proceedings of the VLDB Endowment

    PVLDB · 2 publications · 171 citations

    2

    h-index

  3. 1

    h-index

  4. Computer Graphics Forum

    1 publications · 46 citations

    1

    h-index

  5. Distributed and Parallel Databases

    1 publications · 18 citations

    1

    h-index

1–5