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In vitro convolutional neural networks

Poole, William (2022) In vitro convolutional neural networks. Nature Machine Intelligence, 4 (7). pp. 614-615. ISSN 2522-5839. doi:10.1038/s42256-022-00508-1. https://resolver.caltech.edu/CaltechAUTHORS:20220711-652588000

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Abstract

Neural networks can be implemented by using purified DNA molecules that interact in a test tube. Convolutional neural networks to classify high-dimensional data have now been realized in vitro, in one of the most complex demonstrations of molecular programming so far.


Item Type:Article
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https://doi.org/10.1038/s42256-022-00508-1DOIArticle
https://rdcu.be/cRqpPPublisherFree ReadCube access
ORCID:
AuthorORCID
Poole, William0000-0002-2958-6776
Additional Information:© 2022 Springer Nature Limited. Published 11 July 2022. The author declares no competing interests.
Issue or Number:7
DOI:10.1038/s42256-022-00508-1
Record Number:CaltechAUTHORS:20220711-652588000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220711-652588000
Official Citation:Poole, W. In vitro convolutional neural networks. Nat Mach Intell 4, 614–615 (2022). https://doi.org/10.1038/s42256-022-00508-1
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:115459
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:12 Jul 2022 15:42
Last Modified:29 Jul 2022 16:14

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