Bayesian Model Building
Bayesian Model Building is the systematic process of constructing probabilistic models that incorporate prior knowledge and observed data within a Bayesian framework to infer posterior distributions over unknown parameters.
7.4K
Publications
503.3K
Citations
17.5K
Authors
4.1K
Institutions
Publications per year
2017–2026
2.3K
7.4K
1–5 of 7.4K
17.5K
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19
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4.1K
Duke University
Durham, United States
50 h-index
245 publications
16.4K citations
University College London
London, United Kingdom
43 h-index
180 publications
33.3K citations
Stanford University
Stanford, United States
40 h-index
130 publications
14.8K citations

Imperial College London
London, United Kingdom
39 h-index
130 publications
14.6K citations

University of Amsterdam
Amsterdam, The Netherlands
37 h-index
164 publications
70.2K citations
Texas A&M University
College Station, United States
37 h-index
147 publications
8.5K citations
University of Washington
Seattle, United States
36 h-index
124 publications
7.8K citations

University of Toronto
Toronto, Canada
36 h-index
121 publications
8.8K citations
1–8 of 4.1K
145 publications · 21.2K citations
60
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138 publications · 10K citations
54
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Repository · 165 publications · 8.7K citations
44
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95 publications · 6.1K citations
40
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73 publications · 7.4K citations
38
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1–5