Reservoir Computing

Reservoir Computing is a computational framework for training recurrent neural networks in which a fixed, randomly initialized dynamical system, known as the reservoir, projects input signals into a high-dimensional state space, enabling efficient learning through simple linear readout mechanisms.

1.1K

Publications

69.1K

Citations

3K

Authors

902

Institutions

Publications per year

2017–2026

826

Authors

3K

  1. BS
    Benjamin Schrauwen

    Ghent University, Belgium

    42 publications · 6.8K citations

    27

    h-index

  2. MC
    Miguel C. Soriano

    Institute for Cross-Disciplinary Physics and Complex Systems, Spain

    25 publications · 5K citations

    24

    h-index

  3. PB
    Peter Bienstman

    Ghent University, Belgium

    24 publications · 2.5K citations

    20

    h-index

  4. JD
    Joni Dambre

    Ghent University, Belgium

    23 publications · 4.1K citations

    20

    h-index

  5. IF
    Ingo Fischer

    Institute for Cross-Disciplinary Physics and Complex Systems, Spain

    20 publications · 4.1K citations

    19

    h-index

1–5 of 3K

Venues

  1. 32

    h-index

  2. Nature Communications

    34 publications · 7.2K citations

    28

    h-index

  3. 26

    h-index

  4. Optics Express

    36 publications · 3.4K citations

    24

    h-index

  5. Scientific Reports

    34 publications · 3K citations

    23

    h-index

1–5