Laplace Approximation

Laplace Approximation is a method in Bayesian statistics that approximates a posterior distribution by fitting a Gaussian distribution centered at the mode of the posterior, with precision determined by the curvature of the log-posterior density.

533

Publications

44.7K

Citations

1.2K

Authors

660

Institutions

Publications per year

2017–2026

182

Authors

1.2K

  1. HR
    Håvard Rue

    Norwegian University of Science and Technology, Norway

    16 publications · 7.5K citations

    14

    h-index

  2. FL
    Finn Lindgren

    Norwegian University of Science and Technology, Norway

    6 publications · 1.7K citations

    6

    h-index

  3. RE
    Robert E. Kass

    Carnegie Mellon University, United States

    5 publications · 616 citations

    5

    h-index

  4. VG
    Virgilio Gómez‐Rubio

    University of Castilla-La Mancha, Spain

    5 publications · 302 citations

    5

    h-index

  5. JB
    Joseph B. Kadane

    Carnegie Mellon University, United States

    5 publications · 548 citations

    5

    h-index

1–5 of 1.2K

Venues

  1. arXiv (Cornell University)

    Repository · 24 publications · 1.2K citations

    16

    h-index

  2. Biometrika

    15 publications · 1.3K citations

    15

    h-index

  3. Journal of Computational and Graphical Statistics

    JCGS · 12 publications · 884 citations

    12

    h-index

  4. Journal of the American Statistical Association

    14 publications · 856 citations

    12

    h-index

  5. Statistics in Medicine

    10 publications · 455 citations

    10

    h-index

1–5