Entropy Visualization

Entropy Visualization is a model uncertainty visualization technique that specifically represents the degree of uncertainty in probabilistic predictions by mapping entropy values, derived from the probability distribution over possible outcomes, onto visual variables to enable intuitive interpretation of uncertainty across data instances or model outputs.

4

Publications

78

Citations

11

Authors

10

Institutions

Publications per year

2017–2026

2

Authors

11

  1. AB
    Anys Bacha

    University of Michigan–Dearborn, United States

    1 publications · 17 citations

    1

    h-index

  2. NL
    Nada Lachtar

    University of Michigan–Dearborn, United States

    1 publications · 17 citations

    1

    h-index

  3. YH
    Yang Hong

    University of Oklahoma, United States

    1 publications · 10 citations

    1

    h-index

  4. ES
    Ekrem Serin

    Sabancı Üniversitesi, Türkiye

    1 publications · 14 citations

    1

    h-index

  5. WS
    Wenbin Shi

    Beijing Jiaotong University, China

    1 publications · 10 citations

    1

    h-index

1–5 of 11

Venues

  1. IEEE Embedded Systems Letters

    1 publications · 17 citations

    1

    h-index

  2. IEEE Computer Graphics and Applications

    1 publications · 37 citations

    1

    h-index

  3. Nonlinear Dynamics

    1 publications · 10 citations

    1

    h-index

1–3