计算机科学
标杆管理
人工智能
神经形态工程学
深度学习
构造(python库)
卷积神经网络
机器学习
钥匙(锁)
人工神经网络
软件
程序设计语言
计算机安全
业务
营销
出处
期刊:Neuroinformatics
[Springer Nature]
日期:2019-04-10
卷期号:17 (4): 611-628
被引量:61
标识
DOI:10.1007/s12021-019-09424-z
摘要
NengoDL is a software framework designed to combine the strengths of neuromorphic modelling and deep learning. NengoDL allows users to construct biologically detailed neural models, intermix those models with deep learning elements (such as convolutional networks), and then efficiently simulate those models in an easy-to-use, unified framework. In addition, NengoDL allows users to apply deep learning training methods to optimize the parameters of biological neural models. In this paper we present basic usage examples, benchmarking, and details on the key implementation elements of NengoDL. More details can be found at https://www.nengo.ai/nengo-dl.
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