Sample Path Large Deviations

Sample Path Large Deviations is a theoretical framework within large deviations theory that characterizes the asymptotic probabilities of rare trajectories or paths of stochastic processes by analyzing the exponential decay rates of measures on function spaces, distinguished from pointwise or static large deviations through its focus on the entire temporal evolution of the process.

46

Publications

1.5K

Citations

72

Authors

61

Institutions

Publications per year

2017–2026

4

Authors

72

  1. JB
    José Blanchet

    Columbia University, United States

    2 publications · 35 citations

    2

    h-index

  2. CM
    Claudio Macci

    University of Rome Tor Vergata, Italy

    2 publications · 47 citations

    2

    h-index

  3. PD
    Paul Dupuis

    Brown University, United States

    2 publications · 40 citations

    2

    h-index

  4. BZ
    Bert Zwart

    Centrum Wiskunde & Informatica, Netherlands

    2 publications · 35 citations

    2

    h-index

  5. KR
    Kavita Ramanan

    Brown University, United States

    2 publications · 217 citations

    2

    h-index

1–5 of 72

Venues

  1. The Annals of Applied Probability

    8 publications · 446 citations

    8

    h-index

  2. Queueing Systems

    3 publications · 113 citations

    3

    h-index

  3. Stochastic Processes and their Applications

    2 publications · 112 citations

    2

    h-index

  4. IEEE Transactions on Information Theory

    2 publications · 65 citations

    2

    h-index

  5. The Annals of Probability

    2 publications · 53 citations

    2

    h-index

1–5