Transition Probabilities

Transition Probabilities is a probabilistic parameter in a Profile Hidden Markov Model that specifies the likelihood of transitioning from one state to another within the model’s state graph, distinguishing it from emission probabilities by governing the progression between hidden states rather than the generation of observable symbols.

6K

Publications

340.5K

Citations

14.6K

Authors

3.3K

Institutions

Publications per year

2017–2026

838

Authors

14.6K

  1. JE
    J. E. Lawler

    University of Wisconsin–Madison, United States

    56 publications · 4.3K citations

    34

    h-index

  2. ÉB
    Émile Biémont

    University of Liège, Belgium

    64 publications · 2K citations

    28

    h-index

  3. WL
    W. L. Wiese

    National Institute of Standards and Technology, United States

    34 publications · 2.3K citations

    24

    h-index

  4. PP
    P. Palmeri

    University of Mons, Belgium

    41 publications · 1K citations

    21

    h-index

  5. PQ
    P. Quinet

    University of Mons, Belgium

    48 publications · 1.2K citations

    21

    h-index

1–5 of 14.6K

Venues

  1. The Journal of Chemical Physics

    498 publications · 32.2K citations

    88

    h-index

  2. Physical Review

    116 publications · 14.6K citations

    48

    h-index

  3. The Astrophysical Journal

    ApJ · 145 publications · 6.2K citations

    44

    h-index

  4. The Astrophysical Journal Supplement Series

    70 publications · 5.6K citations

    41

    h-index

  5. Physical review. A, General physics

    93 publications · 6.1K citations

    37

    h-index

1–5