Design of MTJ-Based nonvolatile logic gates for quantized neural networks

Author:

Natsui Masanori,Chiba Tomoki,Hanyu Takahiro

Funder

MEXT

JST OPERA

JSPS KAKENHI

Publisher

Elsevier BV

Subject

General Engineering

Reference32 articles.

1. DoReFa-net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients;Zhou,2016

2. Convolutional Neural Networks Using Logarithmic Data Representation;Miyashita,2016

3. Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations;Hubara,2016

4. Binaryconnect: training deep neural networks with binary weights during propagations;Courbariaux;Adv. Neural Inf. Process. Syst.,2015

5. Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1;Courbariaux,2016

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