Stochastic Error Processing

Stochastic Error Processing is a computational framework within error-based learning that models the probabilistic nature of errors during learning, distinguishing itself from deterministic approaches by incorporating randomness in error detection, correction, and adaptation mechanisms.

9

Publications

576

Citations

27

Authors

24

Institutions

Publications per year

2017–2026

1

Authors

27

  1. PR
    Peter R. Killeen

    Arizona State University, United States

    2 publications · 113 citations

    2

    h-index

  2. TJ
    Thomas J. Taylor

    Arizona State University, United States

    2 publications · 113 citations

    2

    h-index

  3. DG
    Dan Gu

    Yangzhou University, China

    1 publications · 22 citations

    1

    h-index

  4. CU
    C. Urban

    Swiss Center for Electronics and Microtechnology (Switzerland), Switzerland

    1 publications · 145 citations

    1

    h-index

  5. NE
    Neil E. Berthier

    University of Massachusetts Amherst, United States

    1 publications · 53 citations

    1

    h-index

1–5 of 27

Venues

  1. Psychological Review

    2 publications · 113 citations

    2

    h-index

  2. 1

    h-index

  3. European Journal of Taxonomy

    EJT · 1 publications · 188 citations

    1

    h-index

  4. Review of Scientific Instruments

    1 publications · 145 citations

    1

    h-index

  5. Journal of Sensors

    1 publications · 19 citations

    1

    h-index

1–5