Gaussian Variational Approximation
Gaussian Variational Approximation is a variational inference method that employs a Gaussian distribution as the approximating family to model the posterior distribution, distinguished by its assumption of normality and dependence on mean and covariance parameters for tractable Bayesian inference.
186
Publications
10.8K
Citations
404
Authors
220
Institutions
Publications per year
2017–2026
56
Parents
186
Elastic theory of pinned flux lattices
Thierry Giamarchi, Pierre Le Doussal · Physical Review Letters · 1994 · 470 citations · Full text
1–5 of 186
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University of California, Irvine, United States
6 publications · 247 citations
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1–5 of 404
220
Laboratoire de physique des Solides
Orsay, France
6 h-index
11 publications
2.6K citations
University College London
London, United Kingdom
6 h-index
12 publications
613 citations
University of California, Irvine
Irvine, United States
6 h-index
15 publications
599 citations

Centre National de la Recherche Scientifique
Paris, France
6 h-index
11 publications
463 citations
University of Cambridge
Cambridge, United Kingdom
6 h-index
10 publications
1.3K citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
5 h-index
6 publications
198 citations

Imperial College London
London, United Kingdom
5 h-index
10 publications
921 citations
Los Alamos National Laboratory
Los Alamos, United States
5 h-index
11 publications
432 citations
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15 publications · 557 citations
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Repository · 12 publications · 817 citations
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PRE · 10 publications · 419 citations
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PRA · 8 publications · 461 citations
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PRL · 7 publications · 926 citations
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