Calibration Under Model Discrepancy

Calibration Under Model Discrepancy is a Bayesian calibration framework that explicitly accounts for systematic differences between computational models and observed data by incorporating a discrepancy term to ensure statistically coherent uncertainty quantification and parameter inference.

26

Publications

1.5K

Citations

80

Authors

54

Institutions

Publications per year

2017–2026

16

Authors

80

  1. CB
    Curtis B. Storlie

    Los Alamos National Laboratory, United States

    2 publications · 149 citations

    2

    h-index

  2. SM
    Sankaran Mahadevan

    Vanderbilt University, United States

    2 publications · 106 citations

    2

    h-index

  3. PG
    Paul Gardner

    University of Sheffield, United Kingdom

    2 publications · 46 citations

    2

    h-index

  4. RJ
    Robert J. Barthorpe

    University of Sheffield, United Kingdom

    2 publications · 46 citations

    2

    h-index

  5. DW
    David Wagg

    University of Bristol, United Kingdom

    1 publications · 15 citations

    1

    h-index

1–5 of 80

Venues

  1. 3

    h-index

  2. Journal of Mechanical Design

    2 publications · 337 citations

    2

    h-index

  3. Mechanical Systems and Signal Processing

    MSSP · 2 publications · 46 citations

    2

    h-index

  4. Computational Statistics & Data Analysis

    CSDA · 1 publications · 36 citations

    1

    h-index

  5. Statistica Sinica

    1 publications · 12 citations

    1

    h-index

1–5