Bayesian Network Latent Variable Models
Bayesian Network Latent Variable Models is a probabilistic graphical model that integrates latent variables within a directed acyclic graph structure to represent conditional dependencies among observed and unobserved variables under a Bayesian inference framework.
68
Publications
3.4K
Citations
188
Authors
108
Institutions
Publications per year
2017–2026
25
68
1–5 of 68
188
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Hong Kong University of Science and Technology, Hong Kong SAR China
2 publications · 75 citations
2
h-index
1–5 of 188
108

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
3 h-index
5 publications
144 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
3 h-index
5 publications
144 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
3 publications
99 citations
University of Washington
Seattle, United States
3 h-index
5 publications
1.7K citations

University of Edinburgh
Edinburgh, United Kingdom
3 h-index
3 publications
77 citations

University of Freiburg
Freiburg im Breisgau, Germany
2 h-index
8 publications
140 citations

University of Cologne
Cologne, Germany
2 h-index
5 publications
112 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
5 publications
69 citations
1–8 of 108
Repository · 9 publications · 577 citations
9
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3 publications · 74 citations
3
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JAIR · 2 publications · 44 citations
2
h-index
2 publications · 811 citations
2
h-index
TPAMI · 2 publications · 72 citations
2
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1–5