Bayesian Canonical Correlation Analysis
Bayesian Canonical Correlation Analysis is a statistical modeling framework within the class of Bayesian latent variable models that extends classical canonical correlation analysis by incorporating Bayesian inference to estimate latent shared structures between multivariate datasets while quantifying uncertainty through posterior distributions.
16
Publications
805
Citations
53
Authors
24
Institutions
Publications per year
2017–2026
3
16
A Tutorial on Canonical Correlation Methods
ACM Computing Surveys · 2017 · 96 citations · Full text
Sparse Bayesian multiway canonical correlation analysis for EEG pattern recognition
Yu Zhang, Guoxu Zhou, Jing Jin et al. · Neurocomputing · 2016 · 61 citations
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24
Aalto University
Espoo, Finland
5 h-index
24 publications
1K citations
Helsinki Institute for Information Technology
Espoo, Finland
4 h-index
12 publications
681 citations

University of Helsinki
Helsinki, Finland
2 h-index
2 publications
94 citations

University of Manitoba
Winnipeg, Canada
1 h-index
4 publications
44 citations
Duke University
Durham, United States
1 h-index
3 publications
168 citations

Statistical and Applied Mathematical Sciences Institute
Durham, United States
1 h-index
2 publications
112 citations

National Institute of Information and Communications Technology
Tokyo, Japan
1 h-index
1 publications
71 citations
Southwest University of Science and Technology
Mianyang, China
1 h-index
5 publications
305 citations
1–8 of 24
1 publications · 11 citations
1
h-index
1 publications · 11 citations
1
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1 publications · 71 citations
1
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1 publications · 36 citations
1
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Conference · 1 publications · 58 citations
1
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1–5