Bayesian Network Visualization

Bayesian Network Visualization is a methodological framework for visually representing probabilistic dependencies and conditional independence relationships among variables in a Bayesian network, distinguished by its integration of graph-theoretic structures with probabilistic inference to communicate uncertainty in relational data.

25

Publications

931

Citations

79

Authors

38

Institutions

Publications per year

2017–2026

13

Authors

79

  1. QV
    Quan‐Hoang Vuong

    Phenikaa University, Vietnam

    2 publications · 208 citations

    2

    h-index

  2. DP
    Dominik Paprotny

    Delft University of Technology, Netherlands

    2 publications · 61 citations

    2

    h-index

  3. AI
    AISDL

    2 publications · 140 citations

    2

    h-index

  4. JL
    Jussi Lahtinen

    VTT Technical Research Centre of Finland, Finland

    2 publications · 37 citations

    2

    h-index

  5. DW
    D.T.H. Worm

    Delft University of Technology, Netherlands

    2 publications · 61 citations

    2

    h-index

1–5 of 79

Venues

  1. SoftwareX

    2 publications · 61 citations

    2

    h-index

  2. Turizam

    1 publications · 16 citations

    1

    h-index

  3. Ecological Modelling

    1 publications · 22 citations

    1

    h-index

  4. NERC Open Research Archive (Natural Environment Research Council)

    Repository · 1 publications · 52 citations

    1

    h-index

  5. Figshare

    Repository · 1 publications · 16 citations

    1

    h-index

1–5