Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science
出版年份 2018 全文链接
标题
Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science
作者
关键词
-
出版物
Nature Communications
Volume 9, Issue 1, Pages -
出版商
Springer Nature
发表日期
2018-06-13
DOI
10.1038/s41467-018-04316-3
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Ultrastructural evidence for synaptic scaling across the wake/sleep cycle
- (2017) Luisa de Vivo et al. SCIENCE
- Homer1a drives homeostatic scaling-down of excitatory synapses during sleep
- (2017) Graham H. Diering et al. SCIENCE
- A topological insight into restricted Boltzmann machines
- (2016) Decebal Constantin Mocanu et al. MACHINE LEARNING
- Mastering the game of Go with deep neural networks and tree search
- (2016) David Silver et al. NATURE
- No-reference video quality measurement: added value of machine learning
- (2015) Decebal Constantin Mocanu et al. JOURNAL OF ELECTRONIC IMAGING
- Human-level control through deep reinforcement learning
- (2015) Volodymyr Mnih et al. NATURE
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Scientific method: Statistical errors
- (2014) Regina Nuzzo NATURE
- Understanding brain networks and brain organization
- (2014) Luiz Pessoa Physics of Life Reviews
- Searching for exotic particles in high-energy physics with deep learning
- (2014) P. Baldi et al. Nature Communications
- A Neuroevolution Approach to General Atari Game Playing
- (2014) Matthew Hausknecht et al. IEEE Transactions on Computational Intelligence and AI in Games
- All Scale-Free Networks Are Sparse
- (2011) Charo I. Del Genio et al. PHYSICAL REVIEW LETTERS
- A Novel Connectionist System for Unconstrained Handwriting Recognition
- (2009) A. Graves et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Complex brain networks: graph theoretical analysis of structural and functional systems
- (2009) Ed Bullmore et al. NATURE REVIEWS NEUROSCIENCE
- Power-Law Distributions in Empirical Data
- (2009) Aaron Clauset et al. SIAM REVIEW
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