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Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science
Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from the network properties of biological neural networks (e.g. sparsity, scale-freeness), we argue that (contrary to general prac...
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| Pubblicato in: | Nat Commun |
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| Autori principali: | , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Publishing Group UK
2018
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6008460/ https://ncbi.nlm.nih.gov/pubmed/29921910 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-018-04316-3 |
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