Mean Absolute Error

Mean Absolute Error is a forecast verification metric that quantifies the average magnitude of prediction errors by computing the arithmetic mean of absolute differences between predicted and observed values across a set of forecasts.

4.5K

Publications

274K

Citations

16.1K

Authors

4.2K

Institutions

Publications per year

2017–2026

2.6K

Variants

Mae

Authors

16.1K

  1. ÖK
    Özgür Kişi

    Ilia State University, Georgia

    24 publications · 1.3K citations

    20

    h-index

  2. KJ
    Kenneth J. Hoffer

    Fondazione G.B. Bietti, Italy

    12 publications · 720 citations

    12

    h-index

  3. GS
    Giacomo Savini

    Fondazione G.B. Bietti, Italy

    12 publications · 473 citations

    12

    h-index

  4. YN
    Y. Neuvo

    11 publications · 291 citations

    10

    h-index

  5. EJ
    Edward J. Coyle

    Purdue University West Lafayette, United States

    8 publications · 629 citations

    8

    h-index

1–5 of 16.1K

Venues

  1. The Journal of Chemical Physics

    81 publications · 16.7K citations

    44

    h-index

  2. Journal of Cataract & Refractive Surgery

    56 publications · 3.6K citations

    35

    h-index

  3. Journal of Chemical Theory and Computation

    JCTC · 55 publications · 3.8K citations

    35

    h-index

  4. Energies

    62 publications · 3.4K citations

    34

    h-index

  5. IEEE Access

    67 publications · 4.1K citations

    32

    h-index

1–5