Bayesian Uncertainty Estimation
Bayesian Uncertainty Estimation is a probabilistic framework for quantifying measurement uncertainty by updating prior beliefs with observed data through Bayes' theorem to derive a posterior distribution that characterizes the uncertainty in model parameters or predictions.
526
Publications
32.1K
Citations
1.4K
Authors
601
Institutions
Publications per year
2017–2026
210
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1.4K
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Physikalisch-Technische Bundesanstalt
Braunschweig, Germany
14 h-index
23 publications
1.2K citations
National Institute of Standards and Technology
Gaithersburg, United States
13 h-index
38 publications
2.4K citations
Los Alamos National Laboratory
Los Alamos, United States
11 h-index
24 publications
2.4K citations
ETH Zurich
Zurich, Switzerland
11 h-index
27 publications
3.2K citations

University of Thessaly
Volos, Greece
10 h-index
18 publications
551 citations

Delft University of Technology
Delft, The Netherlands
8 h-index
17 publications
1.1K citations
Pontificia Universidad Católica de Chile
Santiago, Chile
8 h-index
9 publications
304 citations
The Ohio State University
Columbus, United States
8 h-index
15 publications
934 citations
1–8 of 601
33 publications · 1.2K citations
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Repository · 30 publications · 1.6K citations
18
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MSSP · 12 publications · 383 citations
12
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11 publications · 394 citations
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9 publications · 1.9K citations
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