Evidence-based Uncertainty Estimation

Evidence-Based Uncertainty Estimation is a methodological framework within uncertainty quantification that derives uncertainty measures through explicit incorporation of empirical evidence, distinguishing itself by grounding uncertainty assessments in observed data rather than solely relying on model priors or parametric assumptions.

26

Publications

1.5K

Citations

76

Authors

41

Institutions

Publications per year

2017–2026

13

Authors

76

  1. RA
    Robert A. Canfield

    U.S. Air Force Institute of Technology, United States

    4 publications · 550 citations

    4

    h-index

  2. RV
    Ramana V. Grandhi

    Wright State University, United States

    4 publications · 550 citations

    4

    h-index

  3. LC
    Lixiong Cao

    Hunan University, China

    3 publications · 89 citations

    3

    h-index

  4. CJ
    Chao Jiang

    Hunan University, China

    2 publications · 99 citations

    2

    h-index

  5. DY
    Dejie Yu

    Hunan University, China

    2 publications · 92 citations

    2

    h-index

1–5 of 76

Venues

  1. Reliability Engineering & System Safety

    5 publications · 453 citations

    5

    h-index

  2. Applied Mathematical Modelling

    2 publications · 72 citations

    2

    h-index

  3. 2

    h-index

  4. Structural and Multidisciplinary Optimization

    2 publications · 77 citations

    2

    h-index

  5. 1

    h-index

1–5