Bayesian Networks

Bayesian Networks is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph, encoding joint probability distributions with local conditional probability specifications.

5.7K

Publications

367.8K

Citations

13.3K

Authors

3.3K

Institutions

Publications per year

2017–2026

1.7K

Authors

13.3K

  1. DK
    Daphne Koller

    Stanford University, United States

    39 publications · 5.7K citations

    32

    h-index

  2. NF
    Nir Friedman

    Hebrew University of Jerusalem, Israel

    40 publications · 8.8K citations

    30

    h-index

  3. NF
    Norman Fenton

    Queen Mary University of London, United Kingdom

    48 publications · 2.9K citations

    29

    h-index

  4. MN
    Martin Neil

    Queen Mary University of London, United Kingdom

    41 publications · 3.2K citations

    28

    h-index

  5. PL
    Pedro Larrañaga

    Universidad Politécnica de Madrid, Spain

    40 publications · 2.3K citations

    23

    h-index

1–5 of 13.3K

Venues

  1. arXiv (Cornell University)

    Repository · 404 publications · 30.2K citations

    71

    h-index

  2. Reliability Engineering & System Safety

    91 publications · 8.8K citations

    53

    h-index

  3. International Journal of Approximate Reasoning

    110 publications · 5.7K citations

    36

    h-index

  4. Bioinformatics

    49 publications · 7.3K citations

    36

    h-index

  5. Expert Systems with Applications

    61 publications · 3.1K citations

    33

    h-index

1–5