Shape Grammar Learning

Shape Grammar Learning is a computational method for inferring generative rules from geometric examples, specifically distinguished by its focus on discovering hierarchical, parameterized shape rules that govern the spatial composition of two-dimensional forms.

22

Publications

1.8K

Citations

59

Authors

40

Institutions

Publications per year

2017–2026

4

Authors

59

  1. GS
    George Stiny

    University of California, Los Angeles, United States

    4 publications · 873 citations

    4

    h-index

  2. OT
    Olivier Teboul

    Google (United States), United States

    3 publications · 241 citations

    3

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  3. NP
    Nikos Paragios

    École Centrale Paris, France

    3 publications · 241 citations

    3

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  4. PK
    Panagiotis Koutsourakis

    École Centrale Paris, France

    3 publications · 241 citations

    3

    h-index

  5. LV
    Luc Van Gool

    ETH Zurich, Switzerland

    2 publications · 155 citations

    2

    h-index

1–5 of 59

Venues

  1. Design Studies

    2 publications · 136 citations

    2

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  2. Research in Engineering Design

    2 publications · 37 citations

    2

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  3. 2

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  4. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 1 publications · 37 citations

    1

    h-index

  5. Journal of Computing in Civil Engineering

    1 publications · 85 citations

    1

    h-index

1–5