Quantum semi-supervised generative adversarial network for enhanced data classification

Abstract In this paper, we propose the quantum semi-supervised generative adversarial network (qSGAN). The system is composed of a quantum generator and a classical discriminator/classifier (D/C). The goal is to train both the generator and the D/C, so that the latter may get a high classification a...

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Auteurs principaux: Kouhei Nakaji, Naoki Yamamoto
Format: article
Langue:EN
Publié: Nature Portfolio 2021
Sujets:
R
Q
Accès en ligne:https://doaj.org/article/28d3e769cea14ac5bf6d99df44acb399
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