Baum-welch Algorithm

The Baum-Welch Algorithm is an expectation-maximization algorithm used to estimate the parameters of a hidden Markov model by iteratively maximizing the likelihood of observed data given the model.

241

Publications

14.9K

Citations

575

Authors

261

Institutions

Publications per year

2017–2026

33

Variants

Baum-welch

Authors

575

  1. HN
    Hermann Ney

    RWTH Aachen University, Germany

    5 publications · 167 citations

    5

    h-index

  2. PK
    Patrick Kenny

    Computer Research Institute of Montréal, Canada

    4 publications · 317 citations

    4

    h-index

  3. AK
    Anders Krogh

    University of Copenhagen, Denmark

    4 publications · 156 citations

    4

    h-index

  4. JH
    Jenq–Neng Hwang

    University of Washington, United States

    4 publications · 87 citations

    4

    h-index

  5. KW
    Kyoung‐Jae Won

    University of Pennsylvania, United States

    4 publications · 156 citations

    4

    h-index

1–5 of 575

Venues

  1. IEEE Transactions on Signal Processing

    11 publications · 673 citations

    11

    h-index

  2. 5

    h-index

  3. BMC Bioinformatics

    4 publications · 168 citations

    4

    h-index

  4. Bioinformatics

    4 publications · 197 citations

    4

    h-index

  5. 4

    h-index

1–5