Bayesian Finite Mixture Models
Bayesian Finite Mixture Model is a probabilistic clustering framework that specifies a finite number of parametric component distributions, combined under a Bayesian paradigm to jointly infer latent cluster assignments and model parameters through posterior distributions.
230
Publications
14.8K
Citations
462
Authors
312
Institutions
Publications per year
2017–2026
44
230
Efficient Bayesian mixed-model analysis increases association power in large cohorts
Po‐Ru Loh, George Tucker, Brendan Bulik‐Sullivan et al. · Nature Genetics · 2015 · 1.8K citations · Full text
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Vienna University of Economics and Business, Austria
6 publications · 130 citations
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312

Concordia University
Montreal, Canada
11 h-index
22 publications
773 citations

Centre National de la Recherche Scientifique
Paris, France
5 h-index
6 publications
96 citations

Queensland University of Technology
Brisbane, Australia
5 h-index
7 publications
267 citations

Université Paris Dauphine-PSL
Paris, France
5 h-index
8 publications
514 citations
Vienna University of Economics and Business
Vienna, Austria
5 h-index
10 publications
229 citations

University of Glasgow
Glasgow, United Kingdom
5 h-index
7 publications
736 citations
Centre de Recherche en Mathématiques de la Décision
Paris, France
5 h-index
8 publications
468 citations

Pennsylvania State University
State College, United States
4 h-index
7 publications
286 citations
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CSDA · 13 publications · 483 citations
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9 publications · 563 citations
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6 publications · 215 citations
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6 publications · 811 citations
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6 publications · 266 citations
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