Efficient Coding Theory

Efficient Coding Theory is a computational theory of neural representation that posits sensory systems evolve to minimize redundancy and maximize information transmission by adapting to the statistical structure of natural stimuli.

145

Publications

8.6K

Citations

341

Authors

193

Institutions

Publications per year

2017–2026

43

Variants

Efficient Coding Hypothesis

Authors

341

  1. AA
    Alan A. Stocker

    University of Pennsylvania, United States

    6 publications · 715 citations

    6

    h-index

  2. VB
    Vijay Balasubramanian

    University of Pennsylvania, United States

    4 publications · 241 citations

    4

    h-index

  3. JT
    Jochen Triesch

    Frankfurt Institute for Advanced Studies, Germany

    4 publications · 87 citations

    4

    h-index

  4. BE
    Bertram E. Shi

    Hong Kong University of Science and Technology, Hong Kong SAR China

    3 publications · 73 citations

    3

    h-index

  5. CF
    Cary Frydman

    University of Southern California, United States

    3 publications · 176 citations

    3

    h-index

1–5 of 341

Venues

  1. Neural Computation

    7 publications · 861 citations

    7

    h-index

  2. PLoS Computational Biology

    5 publications · 178 citations

    5

    h-index

  3. eLife

    4 publications · 193 citations

    4

    h-index

  4. Proceedings of the National Academy of Sciences

    PNAS · 4 publications · 159 citations

    4

    h-index

  5. PLoS ONE

    4 publications · 176 citations

    4

    h-index

1–5