Local Explanations

Local Explanations is a type of interpretability method in machine learning that provides insight into a model's behavior by approximating its decision process in the vicinity of a specific input instance, thereby distinguishing itself from global explanations that aim to characterize overall model behavior.

309

Publications

34.6K

Citations

1K

Authors

470

Institutions

Publications per year

2017–2026

278

Authors

1K

  1. FG
    Fosca Giannotti

    University of Pisa, Italy

    7 publications · 998 citations

    7

    h-index

  2. RG
    Riccardo Guidotti

    University of Pisa, Italy

    7 publications · 1K citations

    7

    h-index

  3. SS
    Sameer Singh

    University of California, Irvine, United States

    6 publications · 7.7K citations

    6

    h-index

  4. AM
    Anna Monreale

    University of Pisa, Italy

    6 publications · 935 citations

    6

    h-index

  5. DP
    Dino Pedreschi

    University of Pisa, Italy

    6 publications · 935 citations

    6

    h-index

1–5 of 1K

Venues

  1. arXiv (Cornell University)

    Repository · 64 publications · 2.8K citations

    28

    h-index

  2. IEEE Access

    11 publications · 861 citations

    10

    h-index

  3. SSRN Electronic Journal

    Repository · 7 publications · 242 citations

    7

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 7 publications · 2.4K citations

    7

    h-index

  5. Applied Sciences

    6 publications · 326 citations

    6

    h-index

1–5