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Main Authors: Matuszewski, Michał, Prystupiuk, Adam, Opala, Andrzej
Format: Recurso digital
Language:English
Published: Zenodo 2024
Online Access:https://doi.org/10.5281/zenodo.10671673
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author Matuszewski, Michał
Prystupiuk, Adam
Opala, Andrzej
author_facet Matuszewski, Michał
Prystupiuk, Adam
Opala, Andrzej
contents <p>Dataset and codes required to reproduce the noise analysis of complex- & real-valued neural networks, as described in the article "Role of all-optical neural-networks" (https://doi.org/10.1103/PhysRevApplied.21.014028)</p> <p>Codes in python require the use of cvnn library published by J. Agustin Barrachina at  <a title="Opens in new tab" href="https://github.com/NEGU93/cvnn/tree/v2.0" target="_blank" rel="noopener">https://github.com/NEGU93/cvnn/tree/v2.0 </a>(URL)</p> <p>We acknowledge support from the National Science Center, Poland under Grants No. 2019/35/N/ST3/01379, No. 2020/37/B/ST3/01657, and No. 2021/43/B/ST3/00752, and the Foundation for Polish Science (FNP).</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_10671673
institution Zenodo
language eng
publishDate 2024
publisher Zenodo
record_format zenodo
spellingShingle Dataset for the "The role of all-optical neural networks" Article
Matuszewski, Michał
Prystupiuk, Adam
Opala, Andrzej
<p>Dataset and codes required to reproduce the noise analysis of complex- & real-valued neural networks, as described in the article "Role of all-optical neural-networks" (https://doi.org/10.1103/PhysRevApplied.21.014028)</p> <p>Codes in python require the use of cvnn library published by J. Agustin Barrachina at  <a title="Opens in new tab" href="https://github.com/NEGU93/cvnn/tree/v2.0" target="_blank" rel="noopener">https://github.com/NEGU93/cvnn/tree/v2.0 </a>(URL)</p> <p>We acknowledge support from the National Science Center, Poland under Grants No. 2019/35/N/ST3/01379, No. 2020/37/B/ST3/01657, and No. 2021/43/B/ST3/00752, and the Foundation for Polish Science (FNP).</p>
title Dataset for the "The role of all-optical neural networks" Article
url https://doi.org/10.5281/zenodo.10671673