Sparse Network Learning
Sparse Network Learning is a machine learning framework that belongs to the class of network inference methods, distinguished by its incorporation of sparsity-inducing constraints or priors to identify minimal sets of significant regulatory interactions from high-dimensional biological data.
222
Publications
13.3K
Citations
972
Authors
365
Institutions
Publications per year
2017–2026
146
Parents
222
New perspectives and methods in link prediction
Ryan N. Lichtenwalter, Jake T. Lussier, Nitesh V. Chawla · 2010 · 673 citations
SGCN:Sparse Graph Convolution Network for Pedestrian Trajectory Prediction
Liushuai Shi, Le Wang, Chengjiang Long et al. · 2021 · 314 citations
1–5 of 222
972
6
h-index
Eindhoven University of Technology, Netherlands
6 publications · 126 citations
6
h-index
4
h-index
4
h-index
4
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1–5 of 972
365
Tsinghua University
Beijing, China
8 h-index
26 publications
1.2K citations

Chinese Academy of Sciences
Beijing, China
6 h-index
19 publications
2.1K citations

Xi'an Jiaotong University
Xi'an, China
5 h-index
14 publications
1.8K citations
Google (United States)
Mountain View, United States
5 h-index
12 publications
994 citations
University of Pennsylvania
Philadelphia, United States
5 h-index
13 publications
330 citations
Indiana University – Purdue University Indianapolis
Indianapolis, United States
4 h-index
18 publications
383 citations
University of Chinese Academy of Sciences
Beijing, China
4 h-index
9 publications
588 citations

University of Twente
Enschede, The Netherlands
4 h-index
8 publications
202 citations
1–8 of 365
Repository · 42 publications · 2.5K citations
24
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7 publications · 228 citations
6
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5 publications · 259 citations
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Conference · 4 publications · 181 citations
4
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3 publications · 154 citations
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1–5