Skeleton Identification

Skeleton Identification is a structural learning method in causal discovery that belongs to the class of graphical model inference techniques, distinguished by its specific aim of recovering the undirected adjacency structure of a causal graph by determining which variables are connected by edges, irrespective of edge orientation.

110

Publications

4.8K

Citations

450

Authors

229

Institutions

Publications per year

2017–2026

40

Authors

450

  1. AH
    Andrew Hill

    Yale University, United States

    2 publications · 88 citations

    2

    h-index

  2. VD
    Vicente de Paulo Emerenciano

    Universidade de São Paulo, Brazil

    2 publications · 24 citations

    2

    h-index

  3. LW
    Lichen Wang

    Northeastern University, United States

    2 publications · 289 citations

    2

    h-index

  4. BS
    Bin Sun

    Northeastern University, United States

    2 publications · 289 citations

    2

    h-index

  5. LK
    Lingyi Kong

    China Pharmaceutical University, China

    2 publications · 44 citations

    2

    h-index

1–5 of 450

Venues

  1. Journal of Natural Products

    4 publications · 120 citations

    4

    h-index

  2. 4

    h-index

  3. Journal of Human Evolution

    JHE · 3 publications · 143 citations

    3

    h-index

  4. Journal of Asian Natural Products Research

    JANPR · 2 publications · 23 citations

    2

    h-index

  5. International Journal of Osteoarchaeology

    2 publications · 97 citations

    2

    h-index

1–5