Machine Learning Model Risk

Machine Learning Model Risk is a type of model risk that arises specifically from the development, deployment, and use of machine learning models, distinguished by uncertainties and potential failures associated with data dependencies, algorithmic complexity, non-linear behavior, and model adaptability in dynamic environments.

115

Publications

7.6K

Citations

571

Authors

255

Institutions

Publications per year

2017–2026

103

Authors

571

  1. HS
    Harini Suresh

    Massachusetts Institute of Technology, United States

    3 publications · 564 citations

    3

    h-index

  2. JV
    John V. Guttag

    Massachusetts Institute of Technology, United States

    3 publications · 564 citations

    3

    h-index

  3. NC
    Nicolò Cesa‐Bianchi

    University of Milan, Italy

    2 publications · 64 citations

    2

    h-index

  4. LC
    Luís Cruz

    Delft University of Technology, Netherlands

    2 publications · 110 citations

    2

    h-index

  5. JL
    Jiangnan Li

    Chinese Academy of Sciences, China

    2 publications · 76 citations

    2

    h-index

1–5 of 571

Venues

  1. arXiv (Cornell University)

    Repository · 11 publications · 800 citations

    11

    h-index

  2. SSRN Electronic Journal

    Repository · 3 publications · 44 citations

    3

    h-index

  3. Journal of Clinical Medicine

    3 publications · 124 citations

    3

    h-index

  4. Journal of Medical Internet Research

    2 publications · 80 citations

    2

    h-index

  5. JAMA Network Open

    2 publications · 215 citations

    2

    h-index

1–5