Bayesian Computation
Bayesian Computation is a branch of statistical computing that focuses on the development and application of computational methods for performing Bayesian inference, distinguished by its reliance on posterior distribution approximation through techniques such as Markov chain Monte Carlo and variational inference.
4.3K
Publications
354.4K
Citations
8.3K
Authors
2.3K
Institutions
Publications per year
2017–2026
1.1K
4.3K
Hierarchical Dirichlet Processes
Yee Whye Teh, Michael I. Jordan, Matthew J. Beal et al. · Journal of the American Statistical Association · 2006 · 3.6K citations
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8.3K
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2.3K

Centre National de la Recherche Scientifique
Paris, France
44 h-index
210 publications
26.7K citations
Duke University
Durham, United States
43 h-index
184 publications
14.2K citations
Stanford University
Stanford, United States
40 h-index
115 publications
12K citations
Massachusetts Institute of Technology
Cambridge, United States
39 h-index
183 publications
13.5K citations
University of Cambridge
Cambridge, United Kingdom
39 h-index
143 publications
13.9K citations

Imperial College London
London, United Kingdom
36 h-index
127 publications
25.9K citations
University of California, Berkeley
Berkeley, United States
35 h-index
120 publications
12.1K citations
University of Oxford
Oxford, United Kingdom
33 h-index
132 publications
33.2K citations
1–8 of 2.3K
119 publications · 31K citations
60
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Repository · 353 publications · 16.1K citations
58
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72 publications · 13.4K citations
40
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44 publications · 11.6K citations
39
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JCGS · 70 publications · 4.7K citations
33
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