Fast and robust analog in-memory deep neural network training
Abstract Analog in-memory computing is a promising future technology for efficiently accelerating deep learning networks. While using in-memory computing to accelerate the inference phase has been studied extensively, accelerating the training phase has received less attention, despite its arguably...
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| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Portfolio
2024-08-01
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| coleção: | Nature Communications |
| Acesso em linha: | https://doi.org/10.1038/s41467-024-51221-z |
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