Gaussian Process Smoothing
Gaussian Process Smoothing is a spatial smoothing method that employs a Gaussian process as a probabilistic model to estimate underlying continuous fields by assigning prior distributions over functions and updating them through observed data.
115
Publications
5.6K
Citations
341
Authors
190
Institutions
Publications per year
2017–2026
43
Parents
115
Tung-Chieh Chen, Zhewei Jiang, Tien-Chang Hsu et al. · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 2008 · 344 citations
Phillip Boyle, Marcus Frean · 2004 · 231 citations
Large Excursions of Gaussian Processes
Mark Kac, D. Slepian · The Annals of Mathematical Statistics · 1959 · 161 citations · Full text
Engineering, Mathematics, Physics +13
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190

National Taiwan University
Taipei, Taiwan
4 h-index
17 publications
2.3K citations
Aalto University
Espoo, Finland
3 h-index
4 publications
249 citations

Chinese Academy of Sciences
Beijing, China
3 h-index
10 publications
259 citations

Cornell University
Ithaca, United States
3 h-index
3 publications
123 citations
University of Sheffield
Sheffield, United Kingdom
3 h-index
8 publications
428 citations
University College London
London, United Kingdom
3 h-index
10 publications
504 citations
Duke University
Durham, United States
3 h-index
3 publications
234 citations

Peking University
Beijing, China
2 h-index
4 publications
244 citations
1–8 of 190
Repository · 7 publications · 194 citations
7
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ApJ · 5 publications · 265 citations
4
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3 publications · 127 citations
3
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2 publications · 52 citations
2
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2 publications · 106 citations
2
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1–5