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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Autores principales: | Kouhei Nakaji, Naoki Yamamoto |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/28d3e769cea14ac5bf6d99df44acb399 |
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