Weight Sparsity
Weight Sparsity is a structural efficiency metric in neural network pruning that quantifies the proportion of zero-valued weights relative to the total number of weights in a model, serving as a measure of model compactness.
70
Publications
3.2K
Citations
297
Authors
101
Institutions
Publications per year
2017–2026
61
Parents
70
JungHoe Kim, Vince D. Calhoun, Eunsoo Shim et al. · NeuroImage · 2015 · 367 citations · Full text
Gregory K. Chen, Raghavan Kumar, H. Ekin Sumbul et al. · IEEE Journal of Solid-State Circuits · 2018 · 206 citations
1–5 of 70
297
6
h-index
Korea Advanced Institute of Science and Technology, South Korea
3 publications · 60 citations
3
h-index
Korea Advanced Institute of Science and Technology, South Korea
3 publications · 60 citations
3
h-index
Korea Advanced Institute of Science and Technology, South Korea
3 publications · 60 citations
3
h-index
3
h-index
1–5 of 297
101
Tsinghua University
Beijing, China
5 h-index
14 publications
465 citations
Massachusetts Institute of Technology
Cambridge, United States
4 h-index
5 publications
286 citations

University of Toronto
Toronto, Canada
3 h-index
12 publications
1K citations
Xiamen University
Xiamen, China
3 h-index
9 publications
675 citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
3 h-index
17 publications
331 citations

Shanghai Jiao Tong University
Shanghai, China
2 h-index
3 publications
266 citations

Chinese Academy of Sciences
Beijing, China
2 h-index
6 publications
155 citations
National Tsing Hua University
Hsinchu, Taiwan
2 h-index
3 publications
114 citations
1–8 of 101
Repository · 13 publications · 590 citations
13
h-index
3 publications · 160 citations
3
h-index
3 publications · 94 citations
3
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2 publications · 32 citations
2
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TPAMI · 2 publications · 82 citations
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