Sparse Network Estimation

Sparse Network Estimation is a statistical inference method that belongs to the class of network estimation techniques, distinguished by its explicit assumption that the underlying ecological interaction network contains relatively few non-zero connections, thereby promoting parsimonious models through regularization or sparsity-inducing constraints.

139

Publications

7K

Citations

383

Authors

203

Institutions

Publications per year

2017–2026

57

Authors

383

  1. ZS
    Zhesi Shen

    Beijing Normal University, China

    5 publications · 315 citations

    5

    h-index

  2. JC
    Jennifer Chayes

    Microsoft (United States), United States

    4 publications · 106 citations

    4

    h-index

  3. AG
    Antonio G. Marqués

    Universidad Rey Juan Carlos, Spain

    4 publications · 71 citations

    4

    h-index

  4. CB
    Christian Borgs

    Microsoft (United States), United States

    4 publications · 106 citations

    4

    h-index

  5. MB
    Matteo Barigozzi

    London School of Economics and Political Science, United Kingdom

    4 publications · 261 citations

    4

    h-index

1–5 of 383

Venues

  1. arXiv (Cornell University)

    Repository · 17 publications · 507 citations

    15

    h-index

  2. IEEE Transactions on Signal Processing

    6 publications · 503 citations

    6

    h-index

  3. Scientific Reports

    4 publications · 171 citations

    4

    h-index

  4. Physical review. E

    PRE · 3 publications · 126 citations

    3

    h-index

  5. Journal of Computational Biology

    3 publications · 62 citations

    3

    h-index

1–5