Sparse Network Inference
Sparse Network Inference is a computational methodology within network inference that specifically aims to reconstruct network structures under the assumption of sparsity, typically by identifying a minimal set of significant interactions among a large number of potential connections.
132
Publications
11.7K
Citations
413
Authors
203
Institutions
Publications per year
2017–2026
76
Parents
132
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413
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203
Massachusetts Institute of Technology
Cambridge, United States
8 h-index
17 publications
4.6K citations
Stanford University
Stanford, United States
5 h-index
13 publications
978 citations

Chinese Academy of Sciences
Beijing, China
5 h-index
13 publications
623 citations
The University of Texas at Austin
Austin, United States
4 h-index
7 publications
296 citations

Centre National de la Recherche Scientifique
Paris, France
4 h-index
9 publications
1.6K citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
15 publications
2.2K citations
University of California, Berkeley
Berkeley, United States
4 h-index
13 publications
310 citations
University of Oxford
Oxford, United Kingdom
4 h-index
8 publications
402 citations
1–8 of 203
Repository · 25 publications · 2.2K citations
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PRE · 5 publications · 268 citations
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4 publications · 194 citations
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LNCS · Book series · 3 publications · 75 citations
3
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Conference · 3 publications · 71 citations
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