Magnitude Thresholding is a model pruning technique that belongs to the class of parameter selection methods by eliminating weights with absolute values below a predetermined threshold, thereby reducing model complexity while preserving significant synaptic contributions.
6
Publications
276
Citations
21
Authors
16
Institutions
Publications per year
2017–2026
2
Parents
Publications
6
Deep learning for magnitude prediction in earthquake early warning
Yanwei Wang, Xiaojun Li, Zifa Wang et al. · Gondwana Research · 2022 · 51 citations
1–5 of 6
Authors
21
- PC
1
h-index
- CICanturk Isci
IBM Research - Thomas J. Watson Research Center, United States
1 publications · 73 citations
1
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- PC
1
h-index
- LW
1
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- MK
1
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1–5 of 21
Institutions
16
Beijing University of Technology
Beijing, China
1 h-index
1 publications
51 citations
Ocean University of China
Qingdao, China
1 h-index
2 publications
88 citations
Princeton University
Princeton, United States
1 h-index
2 publications
146 citations
Qingdao National Laboratory for Marine Science and Technology
Qingdao, China
1 h-index
2 publications
88 citations
Institute of Atmospheric Physics
Beijing, China
1 h-index
1 publications
44 citations
Chinese Academy of Sciences
Beijing, China
1 h-index
1 publications
44 citations
Wayne State University
Detroit, United States
1 h-index
5 publications
185 citations
Université Mustapha Stambouli de Mascara
Mascara, Algeria
1 h-index
1 publications
17 citations
1–8 of 16
Venues
- Journal of Magnetic Resonance Imaging
JMRI · 1 publications · 37 citations
1
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- EURASIP Journal on Image and Video Processing
1 publications · 17 citations
1
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- Expert Systems with Applications
1 publications · 54 citations
1
h-index
- Geoscientific model development
1 publications · 44 citations
1
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- Gondwana Research
1 publications · 51 citations
1
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1–5