Sensitivity Analysis For Surrogates

Sensitivity Analysis for Surrogates is a systematic methodological framework within surrogate modeling that quantifies the influence of individual input variables or parameters on the output variability of a surrogate model, thereby distinguishing itself from general sensitivity analysis by specifically addressing the uncertainties and approximations inherent in surrogate-based predictions.

45

Publications

1.7K

Citations

152

Authors

97

Institutions

Publications per year

2017–2026

22

Authors

152

  1. AM
    Amandine Marrel

    Commissariat à l'Énergie Atomique et aux Énergies Alternatives, France

    2 publications · 69 citations

    2

    h-index

  2. DS
    Davood Shahsavani

    University of Shahrood, Iran

    2 publications · 75 citations

    2

    h-index

  3. XY
    Xinyue Ye

    Kent State University, United States

    1 publications · 67 citations

    1

    h-index

  4. ZZ
    Zhiyuan Zheng

    Beijing Normal University, China

    1 publications · 32 citations

    1

    h-index

  5. AM
    Ali Mehmani

    Columbia University, United States

    1 publications · 50 citations

    1

    h-index

1–5 of 152

Venues

  1. Reliability Engineering & System Safety

    7 publications · 232 citations

    7

    h-index

  2. Structural and Multidisciplinary Optimization

    2 publications · 229 citations

    2

    h-index

  3. Applied Mathematical Modelling

    2 publications · 66 citations

    2

    h-index

  4. Combustion and Flame

    2 publications · 33 citations

    2

    h-index

  5. Journal of Computational Physics

    1 publications · 36 citations

    1

    h-index

1–5