Stochastic Coupling

Stochastic Coupling is a probabilistic technique that constructs joint distributions of two or more stochastic processes in such a way that their marginal distributions remain unchanged while enabling direct comparison through deliberate dependence structure.

123

Publications

5.4K

Citations

278

Authors

171

Institutions

Publications per year

2017–2026

20

Authors

278

  1. WS
    Wilfrid S. Kendall

    University of Warwick, United Kingdom

    6 publications · 169 citations

    6

    h-index

  2. ZW
    Zidong Wang

    Brunel University of London, United Kingdom

    3 publications · 304 citations

    3

    h-index

  3. JD
    Junping Du

    Beijing University of Posts and Telecommunications, China

    2 publications · 34 citations

    2

    h-index

  4. QZ
    Qichun Zhang

    University of Bradford, United Kingdom

    2 publications · 70 citations

    2

    h-index

  5. MJ
    Michael J. Neely

    University of Southern California, United States

    2 publications · 30 citations

    2

    h-index

1–5 of 278

Venues

  1. The Annals of Probability

    4 publications · 217 citations

    4

    h-index

  2. Journal of Applied Probability

    JAP · 3 publications · 100 citations

    3

    h-index

  3. IEEE Transactions on Automatic Control

    3 publications · 419 citations

    3

    h-index

  4. Bernoulli

    3 publications · 49 citations

    3

    h-index

  5. 3

    h-index

1–5