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In this paper, we address the problem how to represent a classical data distribution in a quantum system.
Implementing perceptron models with qubits
RC Wiersema and HJ Kappen · 1905
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John S Bell · 1964
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Ground state of liquid he 4
William Lauchlin McMillan · 1965
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On hidden variables and quantum mechanical probabilities
Eugene P Wigner · 1970
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Completely positive maps and entropy inequalities
Göran Lindblad · 1975
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A learning algorithm for Boltzmann Machines
D. Ackley, G. Hinton, and T. Sejnowski · 1985
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Negative entropy and information in quantum mechanics
Nicolas J Cerf and Chris Adami · 1997
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A decision-theoretic generalization of on-line learning and an application to boosting
Yoav Freund and Robert E Schapire · 1997
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Entropic bell inequalities
N. J. Cerf and C. Adami · 1997
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Quantum annealing in the transverse ising model
Tadashi Kadowaki and Hidetoshi Nishimori · 1998
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Quantum extension of conditional probability
Nicolas J Cerf and Christoph Adami · 1999
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Quantum bayes rule
Ruediger Schack, Todd A Brun, and Carlton M Caves · 2001
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On the problem of hidden variables in quantum mechanics
John S Bell · 2001
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Entropy inequalities
Huzihiro Araki and Elliott H Lieb · 2002
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Quantum, classical, and total amount of correlations in a quantum state
Berry Groisman, Sandu Popescu, and Andreas Winter · 2005
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Classical and quantum correlations under decoherence
J Maziero, L C_ Celeri, RM Serra, and V Vedral · 2009
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Trace inequalities and quantum entropy: an introductory course
Eric Carlen · 2010
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Singular value decomposition and matrix reorderings in quantum information theory
Jarosław Adam Miszczak · 2011
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The classical-quantum boundary for correlations: discord and related measures
Kavan Modi, Aharon Brodutch, Hugo Cable, Tomasz Paterek, and Vlatko Vedral · 2012
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Self-guided quantum tomography
Christopher Ferrie · 2014
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Estimation of effective temperatures in quantum annealers for sampling applications: A case study with possible applications in deep learning
Marcello Benedetti, John Realpe-Gómez, Rupak Biswas, and Alejandro Perdomo-Ortiz · 2016
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Benchmarking quantum hardware for training of fully visible boltzmann machines
Dmytro Korenkevych, Yanbo Xue, Zhengbing Bian, Fabian Chudak, William G Macready, Jason Rolfe, and Evgeny Andriyash · 2016
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Tomography and generative training with quantum boltzmann machines
Mária Kieferová and Nathan Wiebe · 2017
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Solving the quantum many-body problem with artificial neural networks
Giuseppe Carleo and Matthias Troyer · 2017
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Machine learning phases of matter
Juan Carrasquilla and Roger G Melko · 2017
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Quantum versus classical annealing of ising spin glasses
Bettina Heim, Troels F Rønnow, Sergei V Isakov, and Matthias Troyer · 2015
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Application of quantum annealing to training of deep neural networks
Steven H Adachi and Maxwell P Henderson · 2015
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Quantum monte carlo methods for nuclear physics
J Carlson, Stefano Gandolfi, Francesco Pederiva, Steven C Pieper, Rocco Schiavilla, KE Schmidt, and Robert B Wiringa · 2015
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Many-body quantum state tomography with neural networks
Giacomo Torlai, Guglielmo Mazzola, Juan Carrasquilla, Matthias Troyer, Roger Melko, and Giuseppe Carleo · 2017
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Practical adaptive quantum tomography
Christopher Granade, Christopher Ferrie, and Steven T Flammia · 2017
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Foundations of quantum discord
Vlatko Vedral · 2017
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Quantum boltzmann machine
Mohammad H Amin, Evgeny Andriyash, Jason Rolfe, Bohdan Kulchytskyy, and Roger Melko · 2018
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Kosuke Mitarai, Makoto Negoro, Masahiro Kitagawa, and Keisuke Fujii · 2018
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Generative training of quantum boltzmann machines with hidden units
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