Neural networks can learn to utilize correlated auxiliary noise

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 ex...

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Detalles Bibliográficos
Autores principales: Ahmadzadegan, Aida, Simidzija, Petar, Li, Ming, Kempf, Achim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8566565/
https://www.ncbi.nlm.nih.gov/pubmed/34732745
http://dx.doi.org/10.1038/s41598-021-00502-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8566565/
https://www.ncbi.nlm.nih.gov/pubmed/34732745
http://dx.doi.org/10.1038/s41598-021-00502-4

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