Bayesian Calibration

Bayesian Calibration is a statistical inference method that employs Bayesian updating to estimate the posterior distribution of model parameters by systematically adjusting them to reconcile discrepancies between model predictions and observed data while accounting for uncertainties in both.

662

Publications

58K

Citations

2.3K

Authors

854

Institutions

Publications per year

2017–2026

282

Authors

2.3K

  1. MM
    M. Maris

    National Institute for Astrophysics, Italy

    10 publications · 191 citations

    10

    h-index

  2. AS
    A.-S. Suur-Uski

    University of Helsinki, Finland

    10 publications · 191 citations

    10

    h-index

  3. LP
    L. P. L. Colombo

    University of Milan, Italy

    10 publications · 191 citations

    10

    h-index

  4. DH
    D. Herman

    University of Oslo, Norway

    10 publications · 191 citations

    10

    h-index

  5. MB
    M. Brilenkov

    University of Oslo, Norway

    10 publications · 191 citations

    10

    h-index

1–5 of 2.3K

Venues

  1. Water Resources Research

    27 publications · 3K citations

    25

    h-index

  2. 18

    h-index

  3. arXiv (Cornell University)

    Repository · 16 publications · 765 citations

    13

    h-index

  4. Astronomy and Astrophysics

    14 publications · 303 citations

    13

    h-index

  5. Energy and Buildings

    9 publications · 687 citations

    9

    h-index

1–5