Bayesian Brain Models

Bayesian Brain Models is a theoretical framework in neural modeling that posits the brain as a probabilistic inference system, using Bayesian statistics to represent and update beliefs about the environment under uncertainty.

312

Publications

30.4K

Citations

910

Authors

455

Institutions

Publications per year

2017–2026

144

Authors

910

  1. KF
    Karl Friston

    University College London, United Kingdom

    24 publications · 4.9K citations

    21

    h-index

  2. KΕ
    Klaas Ε. Stephan

    University College London, United Kingdom

    11 publications · 2.3K citations

    11

    h-index

  3. CM
    Christoph Mathys

    Institute for Biomedical Engineering, Switzerland

    8 publications · 500 citations

    8

    h-index

  4. WP
    W.D. Penny

    University College London, United Kingdom

    8 publications · 1.6K citations

    8

    h-index

  5. WJ
    Wei Ji

    New York University, United States

    6 publications · 431 citations

    6

    h-index

1–5 of 910

Venues

  1. NeuroImage

    43 publications · 6.5K citations

    33

    h-index

  2. PLoS Computational Biology

    19 publications · 1.6K citations

    17

    h-index

  3. Journal of Neuroscience

    14 publications · 2K citations

    14

    h-index

  4. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 15 publications · 299 citations

    11

    h-index

  5. Frontiers in Computational Neuroscience

    7 publications · 205 citations

    7

    h-index

1–5