Synthesizable Memory Models

Synthesizable Memory Models is a computational framework within memory modeling that enables the systematic generation and integration of diverse memory representations through formally defined, composable operations, distinguishing it from non-synthesizable or ad hoc memory architectures by its emphasis on interoperability, scalability, and theoretical consistency across cognitive and artificial systems.

24

Publications

1.6K

Citations

78

Authors

34

Institutions

Publications per year

2017–2026

4

Authors

78

  1. CW
    Christian Weis

    University of Kaiserslautern, Germany

    3 publications · 64 citations

    3

    h-index

  2. LB
    Luca Benini

    University of Bologna, Italy

    3 publications · 64 citations

    3

    h-index

  3. NW
    Norbert Wehn

    University of Kaiserslautern, Germany

    3 publications · 64 citations

    3

    h-index

  4. IL
    Igor Loi

    University of Bologna, Italy

    3 publications · 64 citations

    3

    h-index

  5. MV
    Martin Vechev

    ETH Zurich, Switzerland

    2 publications · 93 citations

    2

    h-index

1–5 of 78

Venues

  1. UNC Libraries

    Repository · 1 publications · 16 citations

    1

    h-index

  2. 1

    h-index

  3. IEEE Transactions on Circuits and Systems

    1 publications · 117 citations

    1

    h-index

  4. Science

    1 publications · 395 citations

    1

    h-index

  5. ACM SIGPLAN Notices

    1 publications · 17 citations

    1

    h-index

1–5