Pattern-based Generation

Pattern-Based Generation is a methodological construct in computational and cognitive sciences that generates outputs by systematically applying predefined structural regularities, distinguishing it from other generative approaches through its reliance on explicit, rule-based patterns as the primary mechanism for producing novel instances.

36

Publications

1.4K

Citations

101

Authors

53

Institutions

Publications per year

2017–2026

7

Authors

101

  1. JS
    Juergen Schloeffel

    Siemens (Hungary), Hungary

    2 publications · 68 citations

    2

    h-index

  2. AG
    Andreas Glowatz

    University of Bremen, Germany

    2 publications · 68 citations

    2

    h-index

  3. FP
    F. Pachet

    Sony (France), France

    2 publications · 68 citations

    2

    h-index

  4. PR
    Pierre Roy

    Sony Computer Science Laboratories, Japan

    2 publications · 68 citations

    2

    h-index

  5. DC
    D. Cazaly

    Sony (France), France

    2 publications · 68 citations

    2

    h-index

1–5 of 101

Venues

  1. Neurocomputing

    2 publications · 73 citations

    2

    h-index

  2. arXiv (Cornell University)

    Repository · 1 publications · 11 citations

    1

    h-index

  3. Journal of Second Language Writing

    JSLW · 1 publications · 40 citations

    1

    h-index

  4. Biophysical Journal

    1 publications · 157 citations

    1

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 1 publications · 15 citations

    1

    h-index

1–5