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

Authors

502

  1. XS
    Xinyu Shao

    Huazhong University of Science and Technology, China

    6 publications · 414 citations

    6

    h-index

  2. NB
    Nathalie Bartoli

    Office National d'Études et de Recherches Aérospatiales, France

    4 publications · 452 citations

    4

    h-index

  3. HD
    Huachao Dong

    Northwestern Polytechnical University, China

    4 publications · 267 citations

    4

    h-index

  4. BS
    Bruno Sudret

    ETH Zurich, Switzerland

    4 publications · 143 citations

    4

    h-index

  5. AJ
    Andy J. Keane

    University of Southampton, United Kingdom

    4 publications · 2.4K citations

    4

    h-index

1–5 of 502

Venues

  1. Structural and Multidisciplinary Optimization

    15 publications · 707 citations

    13

    h-index

  2. Journal of Mechanical Design

    7 publications · 729 citations

    7

    h-index

  3. Applied Soft Computing

    6 publications · 290 citations

    6

    h-index

  4. 5

    h-index

  5. AIAA Journal

    5 publications · 311 citations

    5

    h-index

1–5