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In this paper, we propose the quantum semi-supervised generative adversarial network (qSGAN).
Quantum random access memory
Vittorio Giovannetti, Seth Lloyd, and Lorenzo Maccone · 2008
Earlier work this paper cites.
Classical simulation of commuting quantum computations implies collapse of the polynomial hierarchy
Michael J Bremner, Richard Jozsa, and Dan J Shepherd · 2011
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Prediction by linear regression on a quantum computer
Maria Schuld, Ilya Sinayskiy, and Francesco Petruccione · 2016
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Average-case complexity versus approximate simulation of commuting quantum computations
Michael J Bremner, Ashley Montanaro, and Dan J Shepherd · 2016
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Quantum supremacy through the quantum approximate optimization algorithm
Edward Farhi and Aram W Harrow · 2016
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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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Semi-supervised learning with generative adversarial networks
Augustus Odena · 2016
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Quantum machine learning
Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd · 2017
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Achieving quantum supremacy with sparse and noisy commuting quantum computations
Michael J Bremner, Ashley Montanaro, and Dan J Shepherd · 2017
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Good semi-supervised learning thataaa requires a bad GAN
Zihang Dai, Zhilin Yang, Fan Yang, William W Cohen, and Russ R Salakhutdinov · 2017
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Learning and inference in hilbert space with quantum graphical models
Siddarth Srinivasan, Carlton Downey, and Byron Boots · 2018
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Quantum machine learning: a classical perspective
Carlo Ciliberto, Mark Herbster, Alessandro Davide Ialongo, Massimiliano Pontil, Andrea Rocchetto, Simone Severini, and Leonard Wossnig · 2018
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Quantum generative adversarial networks
Pierre-Luc Dallaire-Demers and Nathan Killoran · 2018
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Quantum generative adversarial learning
Seth Lloyd and Christian Weedbrook · 2018
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Differentiable learning of quantum circuit born machines
Jin-Guo Liu and Lei Wang · 2018
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Supervised learning with quantum-enhanced feature spaces
Vojtěch Havlíček, Antonio D Córcoles, Kristan Temme, Aram W Harrow, Abhinav Kandala, Jerry M Chow, and Jay M Gambetta · 2019
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Circuit-centric quantum classifiers
Maria Schuld, Alex Bocharov, Krysta M Svore, and Nathan Wiebe · 2020
Closest in time.
Quantum classifier with tailored quantum kernel
Carsten Blank, Daniel K Park, June-Koo Kevin Rhee, and Francesco Petruccione · 2020
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Quantum generative adversarial network for generating discrete distribution
Haozhen Situ, Zhimin He, Yuyi Wang, Lvzhou Li, and Shenggen Zheng · 2020
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Realizing a quantum generative adversarial network using a programmable superconducting processor
Kaixuan Huang, Zheng-An Wang, Chao Song, Kai Xu, Hekang Li, Zhen Wang, Qiujiang Guo, Zixuan Song, Zhi-Bo Liu, Dongning Zheng, et al · 2020
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Quantum generative adversarial networks for learning and loading random distributions
Christa Zoufal, Aurélien Lucchi, and Stefan Woerner · 2019
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Adversarial quantum circuit learning for pure state approximation
Marcello Benedetti, Edward Grant, Leonard Wossnig, and Simone Severini · 2019
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Quantum generative adversarial learning in a superconducting quantum circuit
Ling Hu, Shu-Hao Wu, Weizhou Cai, Yuwei Ma, Xianghao Mu, Yuan Xu, Haiyan Wang, Yipu Song, Dong-Ling Deng, Chang-Ling Zou, and Luyan Sun · 2019
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Learning and inference on generative adversarial quantum circuits
Jinfeng Zeng, Yufeng Wu, Jin-Guo Liu, Lei Wang, and Jiangping Hu · 2019
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Jonathan Romero and Alan Aspuru-Guzik · 2019
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Quantum wasserstein generative adversarial networks
Shouvanik Chakrabarti, Tongyang Yiming, Huang an d Li, Soheil Feizi, and Xiaodi Wu · 2019
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Experimental quantum generative adversarial networks for image generation
He-Liang Huang, Yuxuan Du, Ming Gong, Youwei Zhao, Yulin Wu, Chaoyue Wang, Shaowei Li, Futian Liang, Jin Lin, Yu Xu, et al · 2020
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Experimental demonstration of a quantum generative adversarial network for continuous distributions
Abhinav Anand, Jonathan Romero, Matthias Degroote, and Alán Aspuru-Guzik · 2020
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Quantum state tomography with conditional generative adversarial networks
Shahnawaz Ahmed, Carlos Sánchez Muñoz, Franco Nori, and Anton Frisk Kockum · 2020
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Qugan: A generative adversarial network through quantum states
Samuel A Stein, Betis Baheri, Ray Marie Tischio, Ying Mao, Qiang Guan, Ang Li, Bo Fang, and Shuai Xu · 2020
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Anomaly detection with variational quantum generative adversarial networks
Daniel Herr, Benjamin Obert, and Matthias Rosenkranz · 2020
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Catgan: Category-aware generative adversarial networks with hierarchical evolutionary learning for category text generation
Zhiyue Liu, Jiahai Wang, and Zhiwei Liang · 2020
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A review on generative adversarial networks: Algorithms, theory, and applications
Jie Gui, Zhenan Sun, Yonggang Wen, Dacheng Tao, and Jieping Ye · 2020
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