Random Field Uncertainty Quantification
Random Field Uncertainty Quantification is a formal methodology within stochastic modeling that characterizes and propagates uncertainty in spatially or temporally correlated random fields by quantifying probabilistic variability and statistical dependencies across their domains.
34
Publications
1.2K
Citations
106
Authors
52
Institutions
Publications per year
2017–2026
16
Parents
34
Stratigraphic uncertainty modelling with random field approach
Wenping Gong, Chao Zhao, C. Hsein Juang et al. · Computers and Geotechnics · 2020 · 137 citations
Computing, Earth Sciences, Geology +14
Kai Pöthkow, Britta Weber, Hans‐Christian Hege · Computer Graphics Forum · 2011 · 127 citations
1–5 of 34
106
Laboratoire Modélisation et Simulation Multi-Echelle, France
3 publications · 60 citations
3
h-index
2
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2
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2
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2
h-index
1–5 of 106
52
Laboratoire Modélisation et Simulation Multi-Echelle
Champs-sur-Marne, France
3 h-index
10 publications
188 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
11 publications
185 citations
National Central University
Taoyuan City, Taiwan
3 h-index
4 publications
415 citations
China University of Geosciences
Wuhan, China
2 h-index
8 publications
1K citations
University of California San Diego
San Diego, United States
2 h-index
4 publications
116 citations
University of Michigan
Ann Arbor, United States
2 h-index
2 publications
31 citations
Tongji University
Shanghai, China
2 h-index
4 publications
99 citations
Northwestern University
Evanston, United States
2 h-index
8 publications
412 citations
1–8 of 52
3 publications · 176 citations
3
h-index
3 publications · 97 citations
3
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2 publications · 103 citations
2
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1 publications · 28 citations
1
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Conference · 1 publications · 15 citations
1
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1–5