Pattern Generalization Across Scales

Pattern Generalization Across Scales is a theoretical framework in multi-scale pattern analysis that enables the consistent identification and interpretation of structural regularities across varying spatial, temporal, or hierarchical resolutions by abstracting scale-specific idiosyncrasies into invariant descriptive principles.

14

Publications

1.5K

Citations

32

Authors

16

Institutions

Publications per year

2017–2026

3

Authors

32

  1. YB
    Yonatan Belinkov

    Technion – Israel Institute of Technology, Israel

    2 publications · 86 citations

    2

    h-index

  2. AR
    Amir Rosenfeld

    University of Maryland, College Park, United States

    2 publications · 86 citations

    2

    h-index

  3. GM
    Gary M. Pereira

    Perm State University, Russia

    2 publications · 48 citations

    2

    h-index

  4. NS
    Nir Shavit

    Tel Aviv University, Israel

    2 publications · 86 citations

    2

    h-index

  5. JS
    Jonathan S. Rosenfeld

    Massachusetts Institute of Technology, United States

    2 publications · 86 citations

    2

    h-index

1–5 of 32

Venues

  1. Geographical Analysis

    2 publications · 48 citations

    2

    h-index

  2. Journal of Theoretical Biology

    1 publications · 12 citations

    1

    h-index

  3. Neural Networks

    1 publications · 32 citations

    1

    h-index

  4. American Educational Research Journal

    AERJ · 1 publications · 753 citations

    1

    h-index

  5. Mathematical Thinking and Learning

    1 publications · 35 citations

    1

    h-index

1–5