Entropy-based Representation

Entropy-Based Representation is a formal method for quantifying uncertainty in probabilistic systems by modeling the degree of randomness or unpredictability through information-theoretic entropy measures.

404

Publications

17.9K

Citations

1.1K

Authors

568

Institutions

Publications per year

2017–2026

159

Authors

1.1K

  1. YD
    Yong Deng

    University of Electronic Science and Technology of China, China

    7 publications · 439 citations

    7

    h-index

  2. RR
    Ronald R. Yager

    Iona College, United States

    5 publications · 417 citations

    5

    h-index

  3. RW
    Ross Whitaker

    University of Utah, United States

    5 publications · 305 citations

    5

    h-index

  4. JC
    Joshua Cates

    University of Utah, United States

    4 publications · 270 citations

    4

    h-index

  5. VP
    Vijay P. Singh

    Texas A&M University, United States

    4 publications · 357 citations

    4

    h-index

1–5 of 1.1K

Venues

  1. Entropy

    22 publications · 986 citations

    16

    h-index

  2. IEEE Transactions on Fuzzy Systems

    TFS · 8 publications · 1K citations

    8

    h-index

  3. 8

    h-index

  4. Journal of Hydrology

    6 publications · 605 citations

    6

    h-index

  5. arXiv (Cornell University)

    Repository · 6 publications · 241 citations

    6

    h-index

1–5