Markov Processes

Markov Processes is a stochastic process characterized by the Markov property, which asserts that the future state depends only on the present state and is conditionally independent of the past given the current state.

47.5K

Publications

2.9M

Citations

43.1K

Authors

6.3K

Institutions

Publications per year

2017–2026

5.6K

Authors

43.1K

  1. GO
    Gareth O. Roberts

    University of Warwick, United Kingdom

    80 publications · 13K citations

    46

    h-index

  2. PS
    Peng Shi

    The University of Adelaide, Australia

    79 publications · 6.4K citations

    44

    h-index

  3. SN
    Satya N. Majumdar

    Centre National de la Recherche Scientifique, France

    92 publications · 6.6K citations

    44

    h-index

  4. RL
    Richard L. Tweedie

    Colorado State University, United States

    80 publications · 8.1K citations

    42

    h-index

  5. HK
    Harry Kesten

    Cornell University, United States

    63 publications · 7.1K citations

    40

    h-index

1–5 of 43.1K

Venues

  1. The Annals of Probability

    1.5K publications · 91K citations

    139

    h-index

  2. Journal of the American Statistical Association

    312 publications · 83.8K citations

    105

    h-index

  3. Stochastic Processes and their Applications

    1.3K publications · 59.6K citations

    102

    h-index

  4. Physical Review Letters

    PRL · 364 publications · 38.4K citations

    102

    h-index

  5. Probability Theory and Related Fields

    779 publications · 45.2K citations

    101

    h-index

1–5