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In this work we experimentally demonstrate how generative model training can be used as a benchmark for small ($<5$ qubits) quantum devices.
A kernel method for the two-sample-problem
Arthur Gretton, Karsten M Borgwardt, Malte Rasch, Bernhard Schölkopf, and Alex J Smola · 2007
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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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Learning in implicit generative models
Shakir Mohamed and Balaji Lakshminarayanan · 2016
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Deep learning
Ian Goodfellow, Yoshua Bengio, and Aaron Courville · 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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Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
Abhinav Kandala, Antonio Mezzacapo, Kristan Temme, Maika Takita, Markus Brink, Jerry M Chow, and Jay M Gambetta · 2017
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Benchmarking gate-based quantum computers
Kristel Michielsen, Madita Nocon, Dennis Willsch, Fengping Jin, Thomas Lippert, and Hans De Raedt · 2017
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Hao Li, Zheng Xu, Gavin Taylor, and Tom Goldstein · 2017
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Alejandro Perdomo-Ortiz, Marcello Benedetti, John Realpe-Gómez, and Rupak Biswas · 2018
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Differentiable learning of quantum circuit Born machine
Jin-Guo Liu and Lei Wang · 2018
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A generative modeling approach for benchmarking and training shallow quantum circuits
Marcello Benedetti, Delfina Garcia-Pintos, Yunseong Nam, and Alejandro Perdomo-Ortiz · 2018
Adversarial quantum circuit learning for pure state approximation
Marcello Benedetti, Edward Grant, Leonard Wossnig, and Simone Severini · 2018
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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, et al · 2018
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Learning and inference on generative adversarial quantum circuits
Jinfeng Zeng, Yufeng Wu, Jin-Guo Liu, Lei Wang, and Jiangping Hu · 2018
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Information perspective to probabilistic modeling: Boltzmann machines versus Born machines
Song Cheng, Jing Chen, and Lei Wang · 2018
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IBM Q 16 Melbourne backend specification v1.1.0, 2018
16 qubit backend: IBM Q team · 2018
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Quantum generative adversarial learning
Seth Lloyd and Christian Weedbrook · 2018
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Quantum generative adversarial networks
Pierre-Luc Dallaire-Demers and Nathan Killoran · 2018
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Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks
Pratik Chaudhari and Stefano Soatto · 2018
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Error mitigation extends the computational reach of a noisy quantum processor
Abhinav Kandala, Kristan Temme, Antonio D. Córcoles, Antonio Mezzacapo, Jerry M. Chow, and Jay M. Gambetta · 2019
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