Boss Features

Boss Features is a paper-level academic contribution that constitutes a primary methodological or structural innovation within feature-based modeling, distinguished by its direct subordination to the parent topic and its role in defining the core technical advancement of the work.

9

Publications

252

Citations

14

Authors

8

Institutions

Publications per year

2017–2026

5

Authors

14

  1. CB
    Christophe Balland

    Laboratoire de Physique Nucléaire et de Hautes Énergies, France

    2 publications · 51 citations

    2

    h-index

  2. RP
    Rob Patro

    Stony Brook University, United States

    2 publications · 70 citations

    2

    h-index

  3. MJ
    Mike Joy

    University of Warwick, United Kingdom

    2 publications · 65 citations

    2

    h-index

  4. FA
    Fatemeh Almodaresi

    Stony Brook University, United States

    2 publications · 70 citations

    2

    h-index

  5. PP
    Prashant Pandey

    Stony Brook University, United States

    2 publications · 70 citations

    2

    h-index

1–5 of 14

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 51 citations

    2

    h-index

  2. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)

    Repository · 1 publications · 20 citations

    1

    h-index

  3. Journal of Medical Microbiology

    JMM · 1 publications · 38 citations

    1

    h-index

  4. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 1 publications · 50 citations

    1

    h-index

  5. 1

    h-index

1–5