Structured Variational Inference
Structured Variational Inference is a variational inference method that, unlike mean-field approximations, explicitly incorporates rich dependency structures among latent variables by employing structured variational families guided by the model's conditional independence structure.
37
Publications
3.6K
Citations
116
Authors
54
Institutions
Publications per year
2017–2026
16
Parents
37
Sequential Neural Models with Stochastic Layers
M. Fraccaro, Søren Kaae Sønderby, Ulrich Paquet et al. · arXiv (Cornell University) · 2016 · 161 citations · Full text
A co-inference approach to robust visual tracking
Ying Wu, Thomas S. Huang · 2002 · 127 citations
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University of Edinburgh
Edinburgh, United Kingdom
4 h-index
8 publications
179 citations
Microsoft (United States)
Redmond, United States
2 h-index
2 publications
34 citations

Johns Hopkins University
Baltimore, United States
2 h-index
7 publications
104 citations

Harvard University Press
Cambridge, United States
2 h-index
4 publications
120 citations
New York University
New York, United States
2 h-index
6 publications
1.4K citations
Alphabet (United States)
Mountain View, United States
2 h-index
2 publications
325 citations
University of Copenhagen
Copenhagen, Denmark
2 h-index
2 publications
325 citations
IBM (United States)
Armonk, United States
2 h-index
5 publications
83 citations
1–8 of 54
Repository · 12 publications · 539 citations
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TPAMI · 2 publications · 75 citations
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1 publications · 20 citations
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1 publications · 1.8K citations
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Conference · 1 publications · 21 citations
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