High-dimensional Density Estimation

High-Dimensional Density Estimation is a statistical methodology concerned with inferring the probability density function of a random variable in high-dimensional spaces, where the challenge arises from the curse of dimensionality rendering traditional estimation techniques inefficient or infeasible.

138

Publications

12.9K

Citations

304

Authors

156

Institutions

Publications per year

2017–2026

38

Authors

304

  1. DD
    David Duvenaud

    University of Toronto, Canada

    4 publications · 497 citations

    4

    h-index

  2. WG
    Will Grathwohl

    University of Toronto, Canada

    4 publications · 497 citations

    4

    h-index

  3. MS
    Masashi Sugiyama

    Tokyo Institute of Technology, Japan

    3 publications · 738 citations

    3

    h-index

  4. AG
    Arthur Gretton

    University College London, United Kingdom

    3 publications · 88 citations

    3

    h-index

  5. AP
    Alex Pentland

    Massachusetts Institute of Technology, United States

    3 publications · 1.5K citations

    3

    h-index

1–5 of 304

Venues

  1. arXiv (Cornell University)

    Repository · 23 publications · 1.1K citations

    15

    h-index

  2. The Annals of Statistics

    11 publications · 623 citations

    10

    h-index

  3. 4

    h-index

  4. Journal of Multivariate Analysis

    3 publications · 73 citations

    3

    h-index

  5. Neural Information Processing Systems

    Conference · 3 publications · 105 citations

    3

    h-index

1–5