Probabilistic Programming
Probabilistic Programming is a computational framework that extends general-purpose programming languages with primitives for defining and performing probabilistic inference over expressive probabilistic models, thereby enabling the specification of complex uncertainty representations and reasoning processes through stochastic simulations and Bayesian updating.
593
Publications
55.6K
Citations
1.2K
Authors
495
Institutions
Publications per year
2017–2026
204
593
<i>Stan</i> : A Probabilistic Programming Language
Bob Carpenter, Andrew Gelman, Matthew D. Hoffman et al. · Journal of Statistical Software · 2017 · 7.4K citations · Full text
Stan: A Probabilistic Programming Language
Bob Carpenter, Andrew Gelman, Matthew D. Hoffman et al. · 2017 · 1.3K citations
1–5 of 593
1.2K
14
h-index
13
h-index
Massachusetts Institute of Technology, United States
15 publications · 1.2K citations
12
h-index
11
h-index
11
h-index
1–5 of 1.2K
495
University of Oxford
Oxford, United Kingdom
18 h-index
65 publications
4.3K citations
Stanford University
Stanford, United States
18 h-index
43 publications
4.7K citations
Massachusetts Institute of Technology
Cambridge, United States
17 h-index
57 publications
2.2K citations
KU Leuven
Leuven, Belgium
16 h-index
75 publications
5.7K citations
Microsoft Research (United Kingdom)
Cambridge, United Kingdom
15 h-index
33 publications
1.8K citations

University of Edinburgh
Edinburgh, United Kingdom
15 h-index
22 publications
1K citations
Carnegie Mellon University
Pittsburgh, United States
14 h-index
28 publications
1K citations
Microsoft (United States)
Redmond, United States
13 h-index
32 publications
1.6K citations
1–8 of 495
Repository · 70 publications · 4.3K citations
30
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PACMPL · 27 publications · 869 citations
19
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17 publications · 382 citations
13
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10 publications · 733 citations
10
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Conference · 9 publications · 304 citations
9
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