Functional Data Representation

Functional Data Representation is a mathematical framework that characterizes discrete or irregularly observed data as smooth, continuous functions over a domain, enabling the application of functional analytical techniques by preserving the inherent infinite-dimensional structure of the data.

415

Publications

28.3K

Citations

1K

Authors

531

Institutions

Publications per year

2017–2026

115

Authors

1K

  1. HM
    Hans‐Georg Müller

    University of California, Davis, United States

    10 publications · 651 citations

    10

    h-index

  2. JR
    Juan Romo

    Universidad Carlos III de Madrid, Spain

    9 publications · 1K citations

    9

    h-index

  3. AS
    Anuj Srivastava

    Florida State University, United States

    6 publications · 450 citations

    6

    h-index

  4. SK
    Sebastian Kurtek

    The Ohio State University, United States

    6 publications · 297 citations

    6

    h-index

  5. PV
    Philippe Vieu

    Université Toulouse III - Paul Sabatier, France

    6 publications · 286 citations

    6

    h-index

1–5 of 1K

Venues

  1. Journal of the American Statistical Association

    16 publications · 1.8K citations

    15

    h-index

  2. Computational Statistics & Data Analysis

    CSDA · 13 publications · 1.2K citations

    13

    h-index

  3. Journal of Multivariate Analysis

    12 publications · 417 citations

    12

    h-index

  4. The Annals of Statistics

    11 publications · 1.6K citations

    11

    h-index

  5. arXiv (Cornell University)

    Repository · 11 publications · 455 citations

    10

    h-index

1–5