QEA-QCNN: optimization of quantum convolutional neural network architecture based on quantum evolution-Reference-Cited by-同舟云学术

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QEA-QCNN: optimization of quantum convolutional neural network architecture based on quantum evolution

Published:2024-07-09 Issue:3 Volume:16 Page:233-254
ISSN:1865-9284
Container-title:Memetic Computing
language:en
Short-container-title:Memetic Comp.

Author:

Li Yangyang,Hao Xiaobin,Liu Guanlong,Shang Ronghua,Jiao Licheng

Funder

the Research Project of SongShan Laboratory

the National Natural Science Foundation of China

the Natural Science Basic Research Program of Shaanxi

the Fund for Foreign Scholars in University Research and Teaching Programs

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s12293-024-00417-3.pdf

Reference44 articles.

1. Amin MH, Andriyash E, Rolfe J et al (2018) Quantum boltzmann machine. Phys Rev X 8(2):021050

2. Arufe L, González MA, Oddi A, Rasconi R, Varela R (2022) Quantum circuit compilation by genetic algorithm for quantum approximate optimization algorithm applied to maxcut problem. Swarm Evol Comput 69:101030

3. Biamonte J, Wittek P, Pancotti N et al (2017) Quantum machine learning. Nature 549(7671):195–202

4. Cerezo M, Arrasmith A, Babbush R et al (2021) Variational quantum algorithms. Nature Rev Phys 3(9):625–644

5. Childs AM, Van Dam W (2010) Quantum algorithms for algebraic problems. Rev Mod Phys 82(1):1

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