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The topic area of this paper parameterized quantum circuits (quantum neural networks) which are trained to estimate a given function, specifically the type of circuits proposed by Mitarai et al.
Vychislimoe i nevychislimoe
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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
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Alex Neville, Chris Sparrow, Raphaël Clifford, Eric Johnston, Patrick M Birchall, Ashley Montanaro, and Anthony Laing · 2017
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E Farhi and H Neven · 2018
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Kosuke Mitarai, Makoto Negoro, Masahiro Kitagawa, and Keisuke Fujii · 2018
Circuit-centric quantum classifiers
Maria Schuld, Alex Bocharov, Krysta Svore, and Nathan Wiebe · 2018
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Supervised Learning with Quantum Computers
Maria Schuld and Francesco Petruccione · 2018
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Improvements in quantum sdp-solving with applications
Joran van Apeldoorn and András Gilyén · 2018
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Calculus on parameterized quantum circuits
Javier Gil Vidal and Dirk Oliver Theis · 2018
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Classical algorithms for quantum mean values
Sergey Bravyi, David Gosset, and Ramis Movassagh · 2019
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Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers
Alejandro Perdomo-Ortiz, Marcello Benedetti, John Realpe-Gómez, and Rupak Biswas · 2018
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Analysis on Quantum Circuits
Javier Gil Vidal
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Comparisons of input encodings for quantum neural networks
Andrew W. Lei · 2020
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