Bayesian Variational Inference

Bayesian Variational Inference is a Bayesian approximate inference method that frames posterior estimation as an optimization problem by minimizing the divergence between the true posterior and a tractable variational distribution.

648

Publications

35.9K

Citations

1.7K

Authors

562

Institutions

Publications per year

2017–2026

360

Authors

1.7K

  1. YH
    Yulong Huang

    Harbin Engineering University, China

    14 publications · 2K citations

    14

    h-index

  2. LC
    Lawrence Carin

    Duke University, United States

    14 publications · 613 citations

    13

    h-index

  3. YZ
    Yonggang Zhang

    Harbin Engineering University, China

    12 publications · 2K citations

    12

    h-index

  4. BH
    Biao Huang

    University of Alberta, Canada

    12 publications · 483 citations

    12

    h-index

  5. RM
    Rafael Molina

    Universidad de Granada, Spain

    8 publications · 667 citations

    8

    h-index

1–5 of 1.7K

Venues

  1. arXiv (Cornell University)

    Repository · 70 publications · 3.2K citations

    28

    h-index

  2. IEEE Transactions on Signal Processing

    29 publications · 1.6K citations

    22

    h-index

  3. 13

    h-index

  4. IEEE Transactions on Image Processing

    11 publications · 752 citations

    11

    h-index

  5. 10

    h-index

1–5