Bayesian Confidence Updating
Bayesian Confidence Updating is a computational framework within confidence calibration that formalizes the refinement of probabilistic beliefs through Bayesian inference, distinguishing itself by systematically integrating prior confidence estimates with observed evidence to produce posterior confidence levels in a coherent, normative manner.
66
Publications
3.2K
Citations
205
Authors
146
Institutions
Publications per year
2017–2026
29
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146
University of California, Irvine
Irvine, United States
3 h-index
3 publications
78 citations
University of Illinois Urbana-Champaign
Urbana, United States
3 h-index
3 publications
145 citations

University of Amsterdam
Amsterdam, The Netherlands
3 h-index
3 publications
85 citations
University of Florida
Gainesville, United States
3 h-index
7 publications
229 citations
Stanford University
Stanford, United States
3 h-index
3 publications
289 citations
Michigan State University
East Lansing, United States
2 h-index
3 publications
52 citations

University of East Anglia
Norwich, United Kingdom
2 h-index
2 publications
78 citations
Nanchang University
Nanchang, China
2 h-index
6 publications
459 citations
1–8 of 146
2 publications · 45 citations
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2 publications · 78 citations
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2 publications · 40 citations
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2 publications · 119 citations
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2 publications · 97 citations
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