Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science
Artificial neural networks are artificial intelligence computing methods which are inspired by biological neural networks. Here the authors propose a method to design neural networks as sparse scale-free networks, which leads to a reduction in computational time required for training and inference.
Enregistré dans:
| Auteurs principaux: | , , , , , |
|---|---|
| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2018
|
| Sujets: | |
| Accès en ligne: | https://doaj.org/article/50ee9604a82c41788aeb102570ad016f |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|