Particle Smoothing
Particle Smoothing is a sequential Bayesian inference method that approximates the joint posterior distribution of latent states over a complete observation sequence using a set of weighted particles, distinguished from filtering by incorporating future observations to refine past state estimates.
73
Publications
3.7K
Citations
158
Authors
112
Institutions
Publications per year
2017–2026
11
Variants
Particle Smoother
73
Karl Friston, Klaas Ε. Stephan, Baojuan Li et al. · Mathematical Problems in Engineering · 2010 · 171 citations · Full text
Mike Klaas, Mark Briers, Nando de Freitas et al. · 2006 · 168 citations
Computing, Computer Science, Physics +10
1–5 of 73
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Laboratoire Traitement et Communication de l’Information, France
6 publications · 286 citations
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5
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4
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1–5 of 158
112
University of Cambridge
Cambridge, United Kingdom
11 h-index
19 publications
801 citations

Centre National de la Recherche Scientifique
Paris, France
5 h-index
8 publications
698 citations
Télécom SudParis
Évry-Courcouronnes, France
4 h-index
5 publications
242 citations
Institut Polytechnique de Paris
Palaiseau, France
4 h-index
5 publications
242 citations
University College London
London, United Kingdom
4 h-index
7 publications
812 citations

Linköping University
Linköping, Sweden
4 h-index
7 publications
163 citations
Duke University
Durham, United States
3 h-index
4 publications
234 citations
Laboratoire Traitement et Communication de l’Information
Palaiseau, France
3 h-index
5 publications
374 citations
1–8 of 112
8 publications · 264 citations
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Repository · 4 publications · 93 citations
4
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3 publications · 113 citations
3
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2 publications · 110 citations
2
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1 publications · 103 citations
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