Conditional Typicality

Conditional Typicality is a probabilistic framework in information theory that characterizes the set of sequences jointly typical with a given conditioning sequence, distinguishing itself from standard typicality by incorporating conditional entropy and dependence structure in the typical set definition.

18

Publications

1.4K

Citations

33

Authors

18

Institutions

Publications per year

2017–2026

1

Authors

33

  1. PC
    Paul C. Shields

    University of Toledo, United States

    2 publications · 210 citations

    2

    h-index

  2. IC
    Imre Csiszár

    Hungarian Academy of Sciences, Hungary

    2 publications · 210 citations

    2

    h-index

  3. ER
    Eleanor Rosch

    University of California, Berkeley, United States

    2 publications · 560 citations

    2

    h-index

  4. JB
    James B. Hartle

    University of California, Santa Barbara, United States

    1 publications · 90 citations

    1

    h-index

  5. JJ
    Junekey Jeon

    Korea Advanced Institute of Science and Technology, South Korea

    1 publications · 11 citations

    1

    h-index

1–5 of 33

Venues

  1. Memory & Cognition

    3 publications · 199 citations

    3

    h-index

  2. 2

    h-index

  3. 2

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  4. Technometrics

    2 publications · 36 citations

    2

    h-index

  5. The Annals of Statistics

    1 publications · 178 citations

    1

    h-index

1–5