Bayesian Network Latent Variable Models

Bayesian Network Latent Variable Models is a probabilistic graphical model that integrates latent variables within a directed acyclic graph structure to represent conditional dependencies among observed and unobserved variables under a Bayesian inference framework.

68

Publications

3.4K

Citations

188

Authors

108

Institutions

Publications per year

2017–2026

25

Authors

188

  1. RC
    Rafael Chaves

    Universidade Federal do Rio Grande do Norte, Brazil

    3 publications · 61 citations

    3

    h-index

  2. RP
    Ryan P. Adams

    Harvard University, United States

    2 publications · 106 citations

    2

    h-index

  3. LL
    Lukas Luft

    University of Freiburg, Germany

    2 publications · 35 citations

    2

    h-index

  4. ZZ
    Zhiqiang Zheng

    The University of Texas at Dallas, United States

    2 publications · 58 citations

    2

    h-index

  5. NL
    Nevin L. Zhang

    Hong Kong University of Science and Technology, Hong Kong SAR China

    2 publications · 75 citations

    2

    h-index

1–5 of 188

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 577 citations

    9

    h-index

  2. Bayesian Analysis

    3 publications · 74 citations

    3

    h-index

  3. Journal of Artificial Intelligence Research

    JAIR · 2 publications · 44 citations

    2

    h-index

  4. 2

    h-index

  5. 2

    h-index

1–5