Conditional Realization Generation
Conditional Realization Generation is a stochastic simulation method that produces spatially or temporally consistent realizations of a random field conditioned on observed data, distinguished by its incorporation of auxiliary information to honor both the statistical model and hard constraints.
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Publications
470
Citations
55
Authors
16
Institutions
Publications per year
2017–2026
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University of Sheffield
Sheffield, United Kingdom
2 h-index
6 publications
78 citations

University of Surrey
Guildford, United Kingdom
2 h-index
2 publications
26 citations

University of Aberdeen
Aberdeen, United Kingdom
2 h-index
2 publications
26 citations

Hefei University of Technology
Hefei, China
1 h-index
2 publications
24 citations
State Key Laboratory of Quantum Optics and Quantum Optics Devices
Taiyuan, China
1 h-index
7 publications
133 citations

Heriot-Watt University
Edinburgh, United Kingdom
1 h-index
2 publications
222 citations
Shanxi University
Taiyuan, China
1 h-index
7 publications
133 citations
New Mexico Institute of Mining and Technology
Socorro, United States
1 h-index
2 publications
80 citations
1–8 of 16
Repository · 4 publications · 96 citations
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2 publications · 65 citations
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Repository · 1 publications · 14 citations
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1 publications · 12 citations
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1 publications · 19 citations
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