Nonparametric Bayesian Latent Variable Models

Nonparametric Bayesian Latent Variable Models is a class of probabilistic models that extends traditional latent variable models by employing Bayesian nonparametric methods to automatically infer the complexity or dimensionality of latent structures without pre-specifying fixed parametric forms.

42

Publications

1.8K

Citations

96

Authors

54

Institutions

Publications per year

2017–2026

8

Authors

96

  1. JZ
    Jun Zhu

    Tsinghua University, China

    4 publications · 205 citations

    4

    h-index

  2. DB
    David B. Dunson

    Duke University, United States

    4 publications · 152 citations

    4

    h-index

  3. IV
    Isabel Valera

    Max Planck Institute for Software Systems, Germany

    3 publications · 54 citations

    3

    h-index

  4. TL
    Thomas L. Griffiths

    University of California, Berkeley, United States

    2 publications · 430 citations

    2

    h-index

  5. FY
    Feng Yan

    North China Electric Power University, China

    2 publications · 108 citations

    2

    h-index

1–5 of 96

Venues

  1. arXiv (Cornell University)

    Repository · 8 publications · 229 citations

    8

    h-index

  2. 2

    h-index

  3. Bayesian Analysis

    2 publications · 25 citations

    2

    h-index

  4. Journal of Computational and Graphical Statistics

    JCGS · 2 publications · 131 citations

    2

    h-index

  5. Cambridge University Engineering Department Publications Database

    Repository · 1 publications · 13 citations

    1

    h-index

1–5