High-dimensional Surrogate Modeling
High-Dimensional Surrogate Modeling is a surrogate modeling approach that specifically addresses the challenge of constructing accurate and efficient meta-models in optimization problems characterized by a large number of input variables, where traditional modeling techniques suffer from the curse of dimensionality.
167
Publications
12K
Citations
502
Authors
220
Institutions
Publications per year
2017–2026
113
167
Yinhao Zhu, Nicholas Zabaras, Phaedon‐Stelios Koutsourelakis et al. · Journal of Computational Physics · 2019 · 1K citations · Full text
Computing, Computer Science, Physics +16
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Office National d'Études et de Recherches Aérospatiales, France
4 publications · 452 citations
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1–5 of 502
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Northwestern Polytechnical University
Xi'an, China
13 h-index
41 publications
2.8K citations

Huazhong University of Science and Technology
Wuhan, China
12 h-index
41 publications
2.2K citations

Centre National de la Recherche Scientifique
Paris, France
8 h-index
15 publications
578 citations
Institut Clément Ader
Toulouse, France
6 h-index
15 publications
963 citations
Dalian University of Technology
Dalian, China
6 h-index
25 publications
922 citations
Technical University of Munich
Munich, Germany
5 h-index
10 publications
2.1K citations

Université Toulouse III - Paul Sabatier
Toulouse, France
5 h-index
11 publications
418 citations
University of Michigan
Ann Arbor, United States
4 h-index
7 publications
466 citations
1–8 of 220
15 publications · 707 citations
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7 publications · 729 citations
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6 publications · 290 citations
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6 publications · 329 citations
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5 publications · 311 citations
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