Transferability Analysis

Transferability Analysis is a methodological framework within model calibration that evaluates the generalization capacity of a model’s calibrated predictions across distinct domains, tasks, or datasets by systematically assessing the preservation of calibration properties under distributional shifts.

107

Publications

8.2K

Citations

410

Authors

221

Institutions

Publications per year

2017–2026

54

Authors

410

  1. JP
    Judea Pearl

    University of California, Los Angeles, United States

    6 publications · 737 citations

    6

    h-index

  2. EB
    Elias Bareinboim

    Purdue University West Lafayette, United States

    6 publications · 737 citations

    6

    h-index

  3. TH
    Tal Hassner

    Open University of Israel, Israel

    3 publications · 101 citations

    3

    h-index

  4. CV
    Cuong V. Nguyen

    Amazon (Germany), Germany

    3 publications · 101 citations

    3

    h-index

  5. TM
    Thomas Mensink

    University of Amsterdam, Netherlands

    2 publications · 75 citations

    2

    h-index

1–5 of 410

Venues

  1. 9

    h-index

  2. Molecular Breeding

    3 publications · 124 citations

    3

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 105 citations

    3

    h-index

  4. arXiv (Cornell University)

    Repository · 3 publications · 1.5K citations

    3

    h-index

  5. Journal of Hydrology

    2 publications · 52 citations

    2

    h-index

1–5