Journal article
Hybrid computing using a neural network with dynamic external memory
- Abstract:
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Artificial neural networks are remarkably adept at sensory processing, sequence learning and reinforcement learning, but are limited in their ability to represent variables and data structures and to store data over long timescales, owing to the lack of an external memory. Here we introduce a machine learning model called a differentiable neural computer (DNC), which consists of a neural network that can read from and write to an external memory matrix, analogous to the random-access memory i...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
-
-
(Preview, Accepted manuscript, pdf, 3.4MB, Terms of use)
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- Publisher copy:
- 10.1038/nature20101
Authors
Bibliographic Details
- Publisher:
- Nature Publishing Group
- Journal:
- Nature More from this journal
- Volume:
- 538
- Issue:
- 7626
- Pages:
- 471-476
- Publication date:
- 2016-10-12
- Acceptance date:
- 2016-09-19
- DOI:
- EISSN:
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1476-4687
- ISSN:
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0028-0836
Item Description
- Language:
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English
- Pubs id:
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pubs:653613
- UUID:
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uuid:dd8473bd-2d70-424d-881b-86d9c9c66b51
- Local pid:
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pubs:653613
- Source identifiers:
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653613
- Deposit date:
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2016-11-10
Terms of use
- Copyright holder:
- Graves et al
- Copyright date:
- 2016
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from Nature at: https://doi.org/10.1038/nature20101
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