Robust Uncertainty Analysis

Robust Uncertainty Analysis is a systematic methodological framework within measurement science that characterizes uncertainty in the presence of outliers, model misspecification, or non-ideal data conditions by employing statistical techniques resistant to violations of standard assumptions.

153

Publications

22.8K

Citations

484

Authors

267

Institutions

Publications per year

2017–2026

54

Authors

484

  1. LG
    Lei Gao

    Commonwealth Scientific and Industrial Research Organisation, Australia

    3 publications · 165 citations

    3

    h-index

  2. GS
    Gérard Scorletti

    École Centrale de Lyon, France

    3 publications · 40 citations

    3

    h-index

  3. JR
    Justin Romberg

    Georgia Institute of Technology, United States

    3 publications · 16.4K citations

    3

    h-index

  4. EJ
    Emmanuel J. Candès

    Stanford University, United States

    3 publications · 16.4K citations

    3

    h-index

  5. MH
    Michael H. Ramsey

    University of Sussex, United Kingdom

    3 publications · 223 citations

    3

    h-index

1–5 of 484

Venues

  1. IEEE Transactions on Automatic Control

    5 publications · 541 citations

    5

    h-index

  2. Systems & Control Letters

    4 publications · 139 citations

    4

    h-index

  3. IEEE Transactions on Power Systems

    3 publications · 188 citations

    3

    h-index

  4. AIAA Journal

    3 publications · 410 citations

    3

    h-index

  5. Journal of Sound and Vibration

    JSV · 3 publications · 96 citations

    3

    h-index

1–5