Uncertainty Decomposition

Uncertainty Decomposition is a systematic method within uncertainty analysis that partitions overall uncertainty in a model's output into distinct, interpretable components attributable to specific sources such as model structure, parameters, or input data.

92

Publications

4.4K

Citations

254

Authors

124

Institutions

Publications per year

2017–2026

43

Authors

254

  1. KW
    Karen Willcox

    Massachusetts Institute of Technology, United States

    3 publications · 79 citations

    3

    h-index

  2. DA
    Douglas Allaire

    Texas A&M University, United States

    2 publications · 53 citations

    2

    h-index

  3. HY
    Hui Yin

    Hunan University, China

    2 publications · 30 citations

    2

    h-index

  4. PC
    Pong C. Yuen

    Hong Kong Baptist University, Hong Kong SAR China

    2 publications · 72 citations

    2

    h-index

  5. BY
    Baoyao Yang

    Hong Kong Baptist University, Hong Kong SAR China

    2 publications · 72 citations

    2

    h-index

1–5 of 254

Venues

  1. 6

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  2. arXiv (Cornell University)

    Repository · 4 publications · 117 citations

    4

    h-index

  3. Fuzzy Sets and Systems

    3 publications · 73 citations

    3

    h-index

  4. Water Resources Research

    2 publications · 954 citations

    2

    h-index

  5. 2

    h-index

1–5