Bayesian Latent Variable Models
Bayesian Latent Variable Model is a statistical framework that belongs to the class of Bayesian hierarchical models and is distinguished by its incorporation of unobserved (latent) variables to represent underlying structures or heterogeneity, with inference performed through prior specification and posterior updating via Bayes’ theorem.
592
Publications
35.3K
Citations
1.5K
Authors
698
Institutions
Publications per year
2017–2026
200
Parents
Children
Bayesian Canonical Correlation AnalysisBayesian Dynamic Factor ModelsBayesian Factor AnalysisBayesian Finite Mixture ModelsBayesian Gibbs Sampling For Latent VariablesBayesian Hidden Markov ModelsBayesian Hierarchical Latent Variable ModelsBayesian Latent Class ModelsBayesian Latent Dirichlet AllocationBayesian Latent Gaussian Models
592
1–5 of 592
1.5K
13
h-index
8
h-index
7
h-index
7
h-index
7
h-index
1–5 of 1.5K
698
Duke University
Durham, United States
20 h-index
52 publications
4.9K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
12 h-index
24 publications
643 citations
University of Washington
Seattle, United States
12 h-index
20 publications
8.3K citations
Utrecht University
Utrecht, The Netherlands
11 h-index
25 publications
1.9K citations
Columbia University
New York, United States
11 h-index
16 publications
459 citations
The University of Texas at Austin
Austin, United States
11 h-index
15 publications
1.7K citations
University of Cambridge
Cambridge, United Kingdom
11 h-index
23 publications
1.1K citations
Educational Testing Service
Princeton, United States
11 h-index
12 publications
956 citations
1–8 of 698
23 publications · 853 citations
17
h-index
Repository · 21 publications · 767 citations
16
h-index
18 publications · 507 citations
15
h-index
MBR · 15 publications · 498 citations
14
h-index
16 publications · 3.9K citations
13
h-index
1–5