Annealed Large Deviations

Annealed Large Deviations is a theoretical framework in large deviation theory that characterizes the asymptotic behavior of a system's empirical measures under an averaged (or quenched-averaged) probability measure, where the randomness of the environment is integrated out, distinguishing it from quenched large deviations by considering the joint fluctuations of the system and its random environment.

13

Publications

452

Citations

20

Authors

23

Institutions

Publications per year

2017–2026

0

Authors

20

  1. OZ
    Ofer Zeitouni

    Technion – Israel Institute of Technology, Israel

    4 publications · 204 citations

    4

    h-index

  2. NG
    Nina Gantert

    Technical University of Munich, Germany

    3 publications · 202 citations

    3

    h-index

  3. FC
    Fabienne Castell

    Centre National de la Recherche Scientifique, France

    3 publications · 47 citations

    3

    h-index

  4. WK
    Wolfgang König

    Technische Universität Berlin, Germany

    2 publications · 65 citations

    2

    h-index

  5. JP
    Jonathon Peterson

    Cornell University, United States

    2 publications · 41 citations

    2

    h-index

1–5 of 20

Venues

  1. Probability Theory and Related Fields

    3 publications · 227 citations

    3

    h-index

  2. 3

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  3. arXiv (Cornell University)

    Repository · 2 publications · 28 citations

    2

    h-index

  4. ArXiv.org

    Repository · 1 publications · 27 citations

    1

    h-index

  5. The Annals of Probability

    1 publications · 17 citations

    1

    h-index

1–5