Parameterized Memory Models

Parameterized Memory Models is a computational framework in memory modeling that specifies memory processes through adjustable parameters, distinguishing itself by enabling quantitative predictions of memory behavior across varying experimental conditions via systematic manipulation of its formal parameters.

24

Publications

1.8K

Citations

61

Authors

39

Institutions

Publications per year

2017–2026

4

Authors

61

  1. DG
    Diego Garbervetsky

    Universidad de Buenos Aires, Argentina

    3 publications · 150 citations

    3

    h-index

  2. KK
    Krzysztof Kuchciński

    Lund University, Sweden

    2 publications · 50 citations

    2

    h-index

  3. SY
    Sergio Yovine

    Verimag, France

    2 publications · 110 citations

    2

    h-index

  4. VB
    Vı́ctor Braberman

    Universidad de Buenos Aires, Argentina

    2 publications · 110 citations

    2

    h-index

  5. FF
    F.J. Fernandez

    Leiden University, Netherlands

    2 publications · 112 citations

    2

    h-index

1–5 of 61

Venues

  1. Acta Psychologica

    2 publications · 73 citations

    2

    h-index

  2. The Journal of Object Technology

    JOT · 1 publications · 38 citations

    1

    h-index

  3. Hippocampus

    1 publications · 958 citations

    1

    h-index

  4. European Society for Fuzzy Logic and Technology Conference

    Conference · 1 publications · 15 citations

    1

    h-index

  5. The Journal of Supercomputing

    1 publications · 12 citations

    1

    h-index

1–5