Ensemble Tracking

Ensemble Tracking is a methodological framework within ensemble performance analysis that systematically monitors and evaluates the dynamic interactions and individual contributions of component models over time to assess collective behavior and performance evolution.

20

Publications

1.2K

Citations

68

Authors

33

Institutions

Publications per year

2017–2026

9

Authors

68

  1. BG
    B.J. Geiman

    Duke University, United States

    3 publications · 89 citations

    3

    h-index

  2. NW
    Naiyan Wang

    University of Chinese Academy of Sciences, China

    3 publications · 477 citations

    3

    h-index

  3. DY
    Dit‐Yan Yeung

    Hong Kong University of Science and Technology, Hong Kong SAR China

    3 publications · 477 citations

    3

    h-index

  4. GE
    Gregg E. Trahey

    Duke University, United States

    3 publications · 89 citations

    3

    h-index

  5. LB
    L.N. Bohs

    Duke University, United States

    3 publications · 89 citations

    3

    h-index

1–5 of 68

Venues

  1. 2

    h-index

  2. 2

    h-index

  3. Neurocomputing

    1 publications · 29 citations

    1

    h-index

  4. 1

    h-index

  5. Pattern Recognition

    1 publications · 30 citations

    1

    h-index

1–5