Multi-scale Uncertainty Visualization

Multi-Scale Uncertainty Visualization is a network visualization framework that integrates uncertainty representation across multiple levels of data granularity, enabling the simultaneous depiction of uncertain topological structures at both local and global scales through coordinated visual abstractions.

4

Publications

207

Citations

17

Authors

9

Institutions

Publications per year

2017–2026

2

Authors

17

  1. WN
    Wolfgang Nowak

    University of Stuttgart, Germany

    1 publications · 74 citations

    1

    h-index

  2. DK
    Devinder Kaur

    University of Toledo, United States

    1 publications · 71 citations

    1

    h-index

  3. DG
    David Günther

    Laboratoire Traitement et Communication de l’Information, France

    1 publications · 48 citations

    1

    h-index

  4. MG
    Maksim Gomov

    University of California, Davis, United States

    1 publications · 14 citations

    1

    h-index

  5. RM
    Robert Marinier

    University of Michigan, United States

    1 publications · 71 citations

    1

    h-index

1–5 of 17

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 1 publications · 74 citations

    1

    h-index

  2. Journal of Visualization

    1 publications · 71 citations

    1

    h-index

  3. Computer Graphics Forum

    1 publications · 48 citations

    1

    h-index

  4. IEEE Computer Graphics and Applications

    1 publications · 14 citations

    1

    h-index

  5. Heritage

    1 publications · 11 citations

1–5