Model Confidence Visualization

Model Confidence Visualization is a computational framework that visually represents the degree of certainty or uncertainty associated with the predictions of a machine learning model, distinguishing itself from other visualization techniques by explicitly encoding model confidence through perceptual visual variables.

2

Publications

88

Citations

16

Authors

6

Institutions

Publications per year

2017–2026

2

Authors

16

  1. JS
    Jan S. Kirschke

    Technical University of Munich, Germany

    1 publications · 19 citations

    1

    h-index

  2. LP
    Lace Padilla

    University of California, Merced, United States

    1 publications · 69 citations

    1

    h-index

  3. MP
    Maia Powell

    Northwestern University, United States

    1 publications · 69 citations

    1

    h-index

  4. BM
    Bjoern Menze

    Technical University of Munich, Germany

    1 publications · 19 citations

    1

    h-index

  5. HL
    Hongwei Li

    Technical University of Munich, Germany

    1 publications · 19 citations

    1

    h-index

1–5 of 16

Venues

  1. Frontiers in Neuroscience

    1 publications · 19 citations

    1

    h-index

  2. Frontiers in Psychology

    1 publications · 69 citations

    1

    h-index

1–2