Gaussian Random Field Simulation
Gaussian Random Field Simulation is a conditional simulation method that generates realizations of a spatially correlated random field under the assumption that the underlying distribution is multivariate Gaussian, distinguished by its reliance on Gaussian process theory to model uncertainty and spatial dependence.
143
Publications
10.1K
Citations
304
Authors
200
Institutions
Publications per year
2017–2026
27
Parents
143
1–5 of 143
304
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200
University of Chile
Santiago, Chile
9 h-index
11 publications
635 citations

Centre National de la Recherche Scientifique
Paris, France
5 h-index
8 publications
256 citations
Princeton University
Princeton, United States
5 h-index
8 publications
2.5K citations
The Ohio State University
Columbus, United States
4 h-index
5 publications
231 citations

University of Edinburgh
Edinburgh, United Kingdom
4 h-index
6 publications
212 citations

Bar-Ilan University
Ramat Gan, Israel
4 h-index
6 publications
694 citations

University of Amsterdam
Amsterdam, The Netherlands
3 h-index
6 publications
480 citations
Columbia University
New York, United States
3 h-index
6 publications
144 citations
1–8 of 200
ApJ · 12 publications · 918 citations
12
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8 publications · 895 citations
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6 publications · 169 citations
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CAGEO · 6 publications · 366 citations
6
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4 publications · 509 citations
4
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1–5