Bayesian Model Calibration
Bayesian Model Calibration is a statistical framework that belongs to the class of Bayesian inference methods, distinguished by its incorporation of prior knowledge and observed data to systematically adjust model parameters and quantify uncertainties in order to align model predictions with empirical observations.
415
Publications
29.3K
Citations
1.3K
Authors
603
Institutions
Publications per year
2017–2026
190
Parents
415
Development of the Radiocarbon Calibration Program
Christopher Bronk Ramsey · Radiocarbon · 2001 · 2K citations · Full text
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The University of Texas at Austin
Austin, United States
13 h-index
39 publications
2.7K citations
Los Alamos National Laboratory
Los Alamos, United States
12 h-index
32 publications
1.9K citations
ETH Zurich
Zurich, Switzerland
11 h-index
27 publications
1.2K citations

Vanderbilt University
Nashville, United States
9 h-index
23 publications
814 citations

Centre National de la Recherche Scientifique
Paris, France
9 h-index
19 publications
514 citations
University College London
London, United Kingdom
9 h-index
14 publications
1.3K citations
Sandia National Laboratories California
Livermore, United States
9 h-index
20 publications
732 citations
University of Cambridge
Cambridge, United Kingdom
8 h-index
13 publications
545 citations
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19 publications · 1.1K citations
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12 publications · 1.4K citations
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9 publications · 720 citations
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7 publications · 239 citations
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7 publications · 421 citations
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