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Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science

Nature Communications

Jun 21, 2018

Decebal Constantin MocanuAntonio Liotta

Abstract

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...read more

Mentioned in this Paper

Biological Neural Networks
Anatomical Layer
Metal Working Fluid
Neurons
Family Medicine (Field)
Neural Network Simulation
General Practice (Field)
Learning
Practice Experience
Anatomy, Regional
83
2
2
221
4
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  • Citations1
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Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science

Nature Communications

Jun 21, 2018

Decebal Constantin MocanuAntonio Liotta

PMID: 29921910

DOI: 10.1038/s41467-018-04316-3

Abstract

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...read more

Mentioned in this Paper

Biological Neural Networks
Anatomical Layer
Metal Working Fluid
Neurons
Family Medicine (Field)
Neural Network Simulation
General Practice (Field)
Learning
Practice Experience
Anatomy, Regional
83
2
2
221
4

Feeds With Similar Papers

General Biology Journal eTOCs

Discover the latest general biology research in this collection of the top biology journals.

Neural Networks

Here is the latest research on physiological and in silico networks and circuits implicated in the nervous system.

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Paper Details
References
  • References4
  • Citations1
1

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