Feature Interaction Attribution

Feature Interaction Attribution is an academic method that identifies and quantifies the contribution of interactions among input features to the output of a predictive model, distinguishing it from feature attribution methods that assess individual feature importance in isolation.

6

Publications

252

Citations

15

Authors

9

Institutions

Publications per year

2017–2026

6

Authors

15

  1. PG
    Peyton Greenside

    Stanford University, United States

    2 publications · 103 citations

    2

    h-index

  2. AK
    Anshul Kundaje

    Stanford University, United States

    2 publications · 103 citations

    2

    h-index

  3. TC
    Tyler C. Shimko

    Stanford University, United States

    2 publications · 103 citations

    2

    h-index

  4. PM
    Polly M. Fordyce

    Stanford University, United States

    2 publications · 103 citations

    2

    h-index

  5. AB
    Asa Ben‐Hur

    Colorado State University, United States

    1 publications · 42 citations

    1

    h-index

1–5 of 15

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 77 citations

    2

    h-index

  2. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 1 publications · 11 citations

    1

    h-index

  3. Bioinformatics

    1 publications · 92 citations

    1

    h-index

  4. Nucleic Acids Research

    1 publications · 42 citations

    1

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 1 publications · 12 citations

1–5