Covariance Function Estimation
Covariance Function Estimation is a statistical modeling procedure that identifies the mathematical function characterizing the spatial dependence structure among observations by estimating how covariance varies as a function of distance and direction in a given domain.
284
Publications
22.5K
Citations
551
Authors
336
Institutions
Publications per year
2017–2026
45
Parents
284
Sparse Gaussian Processes using Pseudo-inputs
Edward Snelson, Zoubin Ghahramani · 2005 · 1.3K citations
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Texas A&M University
College Station, United States
10 h-index
17 publications
1.4K citations

Centre National de la Recherche Scientifique
Paris, France
8 h-index
17 publications
513 citations
University of Washington
Seattle, United States
7 h-index
8 publications
1.3K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
7 h-index
10 publications
754 citations
University of Chicago
Chicago, United States
7 h-index
10 publications
643 citations
National University of Singapore
Singapore, Singapore
6 h-index
7 publications
291 citations
University of California, Berkeley
Berkeley, United States
5 h-index
6 publications
556 citations
University of Sheffield
Sheffield, United Kingdom
5 h-index
5 publications
349 citations
1–8 of 336
13 publications · 1.3K citations
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11 publications · 1.2K citations
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10 publications · 1.2K citations
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Repository · 9 publications · 830 citations
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8 publications · 666 citations
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