Bayesian Networks
Bayesian Networks is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph, encoding joint probability distributions with local conditional probability specifications.
5.7K
Publications
367.8K
Citations
13.3K
Authors
3.3K
Institutions
Publications per year
2017–2026
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5.7K
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13.3K
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Stanford University
Stanford, United States
60 h-index
207 publications
28.5K citations
University of Washington
Seattle, United States
38 h-index
124 publications
10.6K citations
Aalborg University
Aalborg, Denmark
35 h-index
103 publications
12.7K citations
Carnegie Mellon University
Pittsburgh, United States
34 h-index
136 publications
9.7K citations
University of California, Los Angeles
Los Angeles, United States
33 h-index
141 publications
8.2K citations
Massachusetts Institute of Technology
Cambridge, United States
33 h-index
112 publications
11K citations
University of California, Berkeley
Berkeley, United States
33 h-index
83 publications
14.6K citations
University of Illinois Urbana-Champaign
Urbana, United States
32 h-index
110 publications
16.7K citations
1–8 of 3.3K
Repository · 404 publications · 30.2K citations
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91 publications · 8.8K citations
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110 publications · 5.7K citations
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49 publications · 7.3K citations
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61 publications · 3.1K citations
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