Prediction Uncertainty Quantification
Prediction Uncertainty Quantification is a methodological framework that characterizes the degree of confidence in forecasted outcomes by systematically assessing sources of variability and error in predictive models within Early Warning Systems.
928
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52.9K
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2.8K
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1.1K
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Publications per year
2017–2026
461
Parents
928
Ben P. Kirtman, Dughong Min, Johnna M. Infanti et al. · Bulletin of the American Meteorological Society · 2013 · 1K citations
Being Sensitive to Uncertainty
Leon Arriola, James M. Hyman · Computing in Science & Engineering · 2007 · 962 citations
The signal and the noise : why so many predictions fail but some don't
Nate Silver · 2012 · 822 citations
Justin Wolfers, Eric Zitzewitz · The Journal of Economic Perspectives · 2004 · 788 citations · Full text
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ETH Zurich
Zurich, Switzerland
14 h-index
26 publications
1.3K citations
Massachusetts Institute of Technology
Cambridge, United States
14 h-index
32 publications
1.5K citations

Centre National de la Recherche Scientifique
Paris, France
13 h-index
21 publications
1.9K citations

Chinese Academy of Sciences
Beijing, China
13 h-index
39 publications
1.9K citations
Stanford University
Stanford, United States
12 h-index
20 publications
1.5K citations
University of Cambridge
Cambridge, United Kingdom
12 h-index
30 publications
1.9K citations
Tsinghua University
Beijing, China
11 h-index
31 publications
1.6K citations
Georgia Institute of Technology
Atlanta, United States
11 h-index
26 publications
1.7K citations
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Repository · 29 publications · 2.5K citations
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Repository · 17 publications · 664 citations
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