Copula Mutual Information

Copula Mutual Information is a measure of statistical dependence between random variables that quantifies their mutual information based on the copula density function, thus capturing the nonlinear and non-Gaussian interdependencies independent of marginal distributions.

31

Publications

1.5K

Citations

93

Authors

61

Institutions

Publications per year

2017–2026

11

Authors

93

  1. RA
    Robin A. A. Ince

    University of Glasgow, United Kingdom

    3 publications · 441 citations

    3

    h-index

  2. SP
    Stefano Panzeri

    Italian Institute of Technology, Italy

    2 publications · 47 citations

    2

    h-index

  3. PG
    Philippe G. Schyns

    University of Glasgow, United Kingdom

    2 publications · 426 citations

    2

    h-index

  4. CK
    Christoph Kayser

    Max Planck Institute for Biological Cybernetics, Germany

    2 publications · 426 citations

    2

    h-index

  5. AO
    Arno Onken

    Italian Institute of Technology, Italy

    2 publications · 47 citations

    2

    h-index

1–5 of 93

Venues

  1. arXiv (Cornell University)

    Repository · 3 publications · 155 citations

    3

    h-index

  2. Journal of Hydrologic Engineering

    1 publications · 59 citations

    1

    h-index

  3. Electronics Letters

    1 publications · 45 citations

    1

    h-index

  4. Revista Colombiana de Estadística

    1 publications · 17 citations

    1

    h-index

  5. NeuroImage

    1 publications · 21 citations

    1

    h-index

1–5