Committee machines—a universal method to deal with non-idealities in memristor-based neural networks
Designing reliable and energy-efficient memristor-based artificial neural networks remains a challenge. Here, the authors demonstrate a technology-agnostic approach, committee machines, which increases the inference accuracy of memristive neural networks that suffer from device variability, faulty d...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2020-08-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-020-18098-0 |