Laplacian Kernels

Laplacian Kernels is a kernel function in the class of positive definite kernels that employs the Laplacian norm to measure similarity between data points, distinguished by its use of the negative exponential of the L1 distance.

305

Publications

19.1K

Citations

715

Authors

399

Institutions

Publications per year

2017–2026

84

Variants

Laplacian Kernel

Authors

715

  1. MS
    Marco Saerens

    UCLouvain, Belgium

    4 publications · 1.4K citations

    4

    h-index

  2. GP
    Giuseppe Patanè

    Istituto di Matematica Applicata e Tecnologie Informatiche, Italy

    4 publications · 61 citations

    4

    h-index

  3. NA
    Nicola Abatangelo

    Université Libre de Bruxelles, Belgium

    3 publications · 79 citations

    3

    h-index

  4. RS
    Raanan Schul

    Stony Brook University, United States

    3 publications · 212 citations

    3

    h-index

  5. KB
    Krzysztof Bogdan

    Wrocław University of Science and Technology, Poland

    3 publications · 333 citations

    3

    h-index

1–5 of 715

Venues

  1. arXiv (Cornell University)

    Repository · 11 publications · 382 citations

    10

    h-index

  2. Journal of Functional Analysis

    8 publications · 791 citations

    8

    h-index

  3. Canadian Journal of Mathematics

    5 publications · 614 citations

    5

    h-index

  4. Transactions of the American Mathematical Society

    TRAN · 5 publications · 139 citations

    5

    h-index

  5. Neurocomputing

    4 publications · 214 citations

    4

    h-index

1–5