Generative Scores

Generative Scores is a methodological framework within instruction-based art that systematizes the transformation of artistic instructions into dynamic, rule-governed procedural outputs through algorithmic interpretation and generative variation.

6

Publications

148

Citations

18

Authors

6

Institutions

Publications per year

2017–2026

2

Authors

18

  1. AB
    Adji Bousso Dieng

    Princeton University, United States

    1 publications · 27 citations

    1

    h-index

  2. XW
    Xiaoyu Wang

    Xidian University, China

    1 publications · 50 citations

    1

    h-index

  3. AC
    Annie Clark

    Upsher-Smith Laboratories (United States), United States

    1 publications · 17 citations

    1

    h-index

  4. MV
    M. V. Mathews

    Stanford University, United States

    1 publications · 22 citations

    1

    h-index

  5. DF
    Dan Friedman

    Yale University, United States

    1 publications · 27 citations

    1

    h-index

1–5 of 18

Venues

  1. British Journal of Clinical Pharmacology

    BJCP · 1 publications · 17 citations

    1

    h-index

  2. Canadian Journal of Philosophy

    CJP · 1 publications · 20 citations

    1

    h-index

  3. Poetics

    1 publications · 12 citations

    1

    h-index

  4. arXiv (Cornell University)

    Repository · 1 publications · 27 citations

    1

    h-index

  5. Perspectives of New Music

    1 publications · 22 citations

    1

    h-index

1–5