Probabilistic Graphical Model Visualization

Probabilistic Graphical Model Visualization is a computational method for representing the structure and probabilistic dependencies of a probabilistic graphical model through visual formalisms such as nodes, edges, and graphical annotations to facilitate interpretation, analysis, and communication of uncertainty and conditional relationships.

24

Publications

1K

Citations

78

Authors

44

Institutions

Publications per year

2017–2026

12

Authors

78

  1. YH
    Yuan He

    Tsinghua University, China

    2 publications · 120 citations

    2

    h-index

  2. YZ
    Yilun Zheng

    Tsinghua University, China

    2 publications · 120 citations

    2

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  3. JB
    João Barros

    Universidade do Porto, Portugal

    2 publications · 36 citations

    2

    h-index

  4. KB
    Karin Binder

    University of Regensburg, Germany

    2 publications · 51 citations

    2

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  5. KB
    Katharina Böcherer-Linder

    University of Kassel, Germany

    2 publications · 82 citations

    2

    h-index

1–5 of 78

Venues

  1. Frontiers in Psychology

    4 publications · 133 citations

    4

    h-index

  2. IEEE Transactions on Network Science and Engineering

    NSE · 1 publications · 21 citations

    1

    h-index

  3. 1

    h-index

  4. Computers & Geosciences

    CAGEO · 1 publications · 31 citations

    1

    h-index

  5. 1

    h-index

1–5