Recurrent Neural Integration

Recurrent Neural Integration is a computational framework within neural network modeling that integrates information across sequential inputs by employing recurrent connections, enabling dynamic state maintenance and temporal dependency learning in contrast to feedforward integration mechanisms.

73

Publications

4.5K

Citations

274

Authors

133

Institutions

Publications per year

2017–2026

45

Authors

274

  1. SB
    Simon B. Laughlin

    University of Cambridge, United Kingdom

    4 publications · 257 citations

    4

    h-index

  2. HS
    Huyin Su

    Huazhong University of Science and Technology, China

    2 publications · 82 citations

    2

    h-index

  3. HL
    Huan Liu

    Huazhong University of Science and Technology, China

    2 publications · 82 citations

    2

    h-index

  4. JT
    Jiang Tang

    Huazhong University of Science and Technology, China

    2 publications · 82 citations

    2

    h-index

  5. LL
    Long Li

    Shanghai University, China

    2 publications · 82 citations

    2

    h-index

1–5 of 274

Venues

  1. Journal of Comparative Physiology A

    4 publications · 257 citations

    4

    h-index

  2. Expert Systems with Applications

    3 publications · 231 citations

    3

    h-index

  3. Journal of Neuroscience

    2 publications · 159 citations

    2

    h-index

  4. Water Resources Management

    2 publications · 134 citations

    2

    h-index

  5. Environmental Science and Pollution Research

    ESPR · 2 publications · 262 citations

    2

    h-index

1–5