Activation Vectors

Activation Vectors is a computational framework that identifies and quantifies directional influences within neural network activations to enable targeted model behavior modification during appliance activation processes.

57

Publications

6.2K

Citations

219

Authors

88

Institutions

Publications per year

2017–2026

31

Authors

219

  1. BK
    Been Kim

    Google (United States), United States

    3 publications · 1.2K citations

    3

    h-index

  2. MW
    Martin Wattenberg

    IBM (United States), United States

    2 publications · 1.2K citations

    2

    h-index

  3. TF
    Tommaso Furlanello

    University of Southern California, United States

    2 publications · 93 citations

    2

    h-index

  4. CJ
    Carrie J. Cai

    Google (United States), United States

    2 publications · 1.2K citations

    2

    h-index

  5. CY
    Chih‐Kuan Yeh

    Carnegie Mellon University, United States

    2 publications · 89 citations

    2

    h-index

1–5 of 219

Venues

  1. arXiv (Cornell University)

    Repository · 7 publications · 1.4K citations

    7

    h-index

  2. Neural Computing and Applications

    3 publications · 287 citations

    3

    h-index

  3. 3

    h-index

  4. Neurocomputing

    2 publications · 195 citations

    2

    h-index

  5. Philosophy and Phenomenological Research

    PPR · 2 publications · 21 citations

    2

    h-index

1–5