Neural networks can learn to utilize correlated auxiliary noise
Abstract We demonstrate that neural networks that process noisy data can learn to exploit, when available, access to auxiliary noise that is correlated with the noise on the data. In effect, the network learns to use the correlated auxiliary noise as an approximate key to decipher its noisy input da...
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Nature Portfolio
2021
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oai:doaj.org-article:07ae4c39ed6948fc946153bd50bfec102021-11-08T10:47:32ZNeural networks can learn to utilize correlated auxiliary noise10.1038/s41598-021-00502-42045-2322https://doaj.org/article/07ae4c39ed6948fc946153bd50bfec102021-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-00502-4https://doaj.org/toc/2045-2322Abstract We demonstrate that neural networks that process noisy data can learn to exploit, when available, access to auxiliary noise that is correlated with the noise on the data. In effect, the network learns to use the correlated auxiliary noise as an approximate key to decipher its noisy input data. An example of naturally occurring correlated auxiliary noise is the noise due to decoherence. Our results could, therefore, also be of interest, for example, for machine-learned quantum error correction.Aida AhmadzadeganPetar SimidzijaMing LiAchim KempfNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021) |
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Medicine R Science Q Aida Ahmadzadegan Petar Simidzija Ming Li Achim Kempf Neural networks can learn to utilize correlated auxiliary noise |
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Abstract We demonstrate that neural networks that process noisy data can learn to exploit, when available, access to auxiliary noise that is correlated with the noise on the data. In effect, the network learns to use the correlated auxiliary noise as an approximate key to decipher its noisy input data. An example of naturally occurring correlated auxiliary noise is the noise due to decoherence. Our results could, therefore, also be of interest, for example, for machine-learned quantum error correction. |
format |
article |
author |
Aida Ahmadzadegan Petar Simidzija Ming Li Achim Kempf |
author_facet |
Aida Ahmadzadegan Petar Simidzija Ming Li Achim Kempf |
author_sort |
Aida Ahmadzadegan |
title |
Neural networks can learn to utilize correlated auxiliary noise |
title_short |
Neural networks can learn to utilize correlated auxiliary noise |
title_full |
Neural networks can learn to utilize correlated auxiliary noise |
title_fullStr |
Neural networks can learn to utilize correlated auxiliary noise |
title_full_unstemmed |
Neural networks can learn to utilize correlated auxiliary noise |
title_sort |
neural networks can learn to utilize correlated auxiliary noise |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/07ae4c39ed6948fc946153bd50bfec10 |
work_keys_str_mv |
AT aidaahmadzadegan neuralnetworkscanlearntoutilizecorrelatedauxiliarynoise AT petarsimidzija neuralnetworkscanlearntoutilizecorrelatedauxiliarynoise AT mingli neuralnetworkscanlearntoutilizecorrelatedauxiliarynoise AT achimkempf neuralnetworkscanlearntoutilizecorrelatedauxiliarynoise |
_version_ |
1718442585630965760 |