Conditional Density Estimation

Conditional Density Estimation is a probabilistic modeling task that belongs to the class of density estimation methods, distinguished by its focus on estimating the probability distribution of a target variable given the observed values of input or conditioning variables.

679

Publications

43.7K

Citations

1.3K

Authors

607

Institutions

Publications per year

2017–2026

108

Authors

1.3K

  1. AL
    Ali Laksaci

    Université Djilali de Sidi Bel Abbès, Algeria

    8 publications · 287 citations

    8

    h-index

  2. BC
    Barry C. Arnold

    University of California, Riverside, United States

    8 publications · 737 citations

    8

    h-index

  3. MR
    Mustapha Rachdi

    Université Grenoble Alpes, France

    6 publications · 192 citations

    6

    h-index

  4. DB
    David B. Dunson

    Duke University, United States

    6 publications · 341 citations

    6

    h-index

  5. RI
    Rafael Izbicki

    Universidade Federal de São Carlos, Brazil

    5 publications · 181 citations

    5

    h-index

1–5 of 1.3K

Venues

  1. arXiv (Cornell University)

    Repository · 31 publications · 885 citations

    17

    h-index

  2. Journal of the American Statistical Association

    19 publications · 2.1K citations

    16

    h-index

  3. Communication in Statistics- Theory and Methods

    14 publications · 267 citations

    12

    h-index

  4. Computational Statistics & Data Analysis

    CSDA · 13 publications · 613 citations

    12

    h-index

  5. IEEE Transactions on Information Theory

    12 publications · 591 citations

    12

    h-index

1–5