Robust Surrogate Modeling
Robust Surrogate Modeling is a computational modeling approach that belongs to the class of surrogate modeling techniques, distinguished by its explicit incorporation of uncertainty quantification and robustness criteria to ensure reliable performance predictions under input variability and model approximation errors.
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4.3K
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251
Authors
129
Institutions
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2017–2026
44
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Enablers for robust POD models
Michel Bergmann, Charles‐Henri Bruneau, Angelo Iollo · Journal of Computational Physics · 2008 · 320 citations · Full text
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Dalian University of Technology
Dalian, China
4 h-index
17 publications
1K citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
5 publications
1.1K citations

Leibniz University Hannover
Hanover, Germany
3 h-index
6 publications
110 citations
University of California, Berkeley
Berkeley, United States
3 h-index
7 publications
182 citations

Petroleum University of Technology
Tehran, Iran
3 h-index
4 publications
156 citations
Universiti Putra Malaysia
Seri Kembangan, Malaysia
2 h-index
8 publications
316 citations
Hartford Financial Services (United States)
Hartford, United States
2 h-index
6 publications
147 citations
University of Virginia
Charlottesville, United States
2 h-index
1 publications
19 citations
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4 publications · 136 citations
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3 publications · 510 citations
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3 publications · 84 citations
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3 publications · 251 citations
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