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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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| Publicado no: | Nat Commun |
|---|---|
| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Publishing Group UK
2018
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| Assuntos: | |
| Acesso em linha: | 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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