Bayesian Decision Theory
Bayesian Decision Theory is a branch of decision theory that employs Bayesian inference to determine optimal decisions under uncertainty by updating prior beliefs with observed data to minimize expected loss or maximize expected utility.
3K
Publications
221.9K
Citations
5.2K
Authors
1.8K
Institutions
Publications per year
2017–2026
610
Variants
Bayesian Decision Analysis
3K
1–5 of 3K
5.2K
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1.8K
University College London
London, United Kingdom
34 h-index
118 publications
13.7K citations
Stanford University
Stanford, United States
31 h-index
71 publications
5K citations
Carnegie Mellon University
Pittsburgh, United States
30 h-index
73 publications
6.1K citations
University of California, Berkeley
Berkeley, United States
27 h-index
60 publications
7.8K citations
Duke University
Durham, United States
26 h-index
61 publications
4.1K citations
Princeton University
Princeton, United States
24 h-index
43 publications
4.9K citations

Centre National de la Recherche Scientifique
Paris, France
24 h-index
63 publications
3.6K citations
Massachusetts Institute of Technology
Cambridge, United States
24 h-index
59 publications
4.3K citations
1–8 of 1.8K
53 publications · 9.2K citations
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Repository · 78 publications · 5.5K citations
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38 publications · 5.5K citations
27
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27 publications · 2.2K citations
24
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26 publications · 2.2K citations
21
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