Robust high-dimensional memory-augmented neural networks
The implementation of memory-augmented neural networks using conventional computer architectures is challenging due to a large number of read and write operations. Here, Karunaratne, Schmuck et al. propose an architecture that enables analog in-memory computing on high-dimensional vectors at accurac...
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Auteurs principaux: | Geethan Karunaratne, Manuel Schmuck, Manuel Le Gallo, Giovanni Cherubini, Luca Benini, Abu Sebastian, Abbas Rahimi |
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Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
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Sujets: | |
Accès en ligne: | https://doaj.org/article/b553751b28d34003af781f5a72f0719a |
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