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We argue that an excess in entanglement between the visible and hidden units in a Quantum Neural Network can hinder learning.
Quantum signatures of chaos
Fritz Haake · 1991
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Entanglement and the foundations of statistical mechanics
Sandu Popescu, Anthony J Short, and Andreas Winter · 2006
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Are random pure states useful for quantum computation?
Michael J. Bremner, Caterina Mora, and Andreas Winter · 2009
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Most quantum states are too entangled to be useful as computational resources
D. Gross, S. T. Flammia, and J. Eisert · 2009
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Large deviation bounds for k-designs
Richard A Low · 2009
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Random quantum circuits are approximate 2-designs
Aram W Harrow and Richard A Low · 2009
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Colloquium: Area laws for the entanglement entropy
Jens Eisert, Marcus Cramer, and Martin B Plenio · 2010
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Quantum principal component analysis
Seth Lloyd, Masoud Mohseni, and Patrick Rebentrost · 2014
Earlier work this paper cites.
Quantum support vector machine for big data classification
Patrick Rebentrost, Masoud Mohseni, and Seth Lloyd · 2014
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The quest for a quantum neural network
Maria Schuld, Ilya Sinayskiy, and Francesco Petruccione · 2014
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Near-linear constructions of exact unitary 2-designs
Richard Cleve, Debbie Leung, Li Liu, and Chunhao Wang · 2015
Earlier work this paper cites.
Chemical basis of trotter-suzuki errors in quantum chemistry simulation
Ryan Babbush, Jarrod McClean, Dave Wecker, Alán Aspuru-Guzik, and Nathan Wiebe · 2015
Cited alongside, same era.
Quantum deep learning
Nathan Wiebe, Ashish Kapoor, and Krysta M Svore · 2016
Cited alongside, same era.
Tomography and generative training with quantum boltzmann machines
Mária Kieferová and Nathan Wiebe · 2017
Cited alongside, same era.
Classification with quantum neural networks on near term processors
Edward Farhi and Hartmut Neven · 2018
Cited alongside, same era.
Quantum-inspired classical algorithms for principal component analysis and supervised clustering
Ewin Tang · 2018
Cited alongside, same era.
Generative training of quantum boltzmann machines with hidden units
Nathan Wiebe and Leonard Wossnig · 2019
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A quantum-inspired classical algorithm for recommendation systems
Ewin Tang · 2019
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Machine learning meets quantum physics
Sankar Das Sarma, Dong-Ling Deng, and Lu-Ming Duan · 2019
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Closing gaps of a quantum advantage with short-time hamiltonian dynamics
Jonas Haferkamp, Dominik Hangleiter, Adam Bouland, Bill Fefferman, Jens Eisert, and Juani Bermejo-Vega · 2019
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An initialization strategy for addressing barren plateaus in parametrized quantum circuits
Edward Grant, Leonard Wossnig, Mateusz Ostaszewski, and Marcello Benedetti · 2019
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András Gilyén, Seth Lloyd, and Ewin Tang · 2018
Cited alongside, same era.
Barren plateaus in quantum neural network training landscapes
Jarrod R McClean, Sergio Boixo, Vadim N Smelyanskiy, Ryan Babbush, and Hartmut Neven · 2018
Cited alongside, same era.
Quantum boltzmann machine
Mohammad H Amin, Evgeny Andriyash, Jason Rolfe, Bohdan Kulchytskyy, and Roger Melko · 2018
Cited alongside, same era.
Aram Harrow and Saeed Mehraban · 2018
Cited alongside, same era.
Quantum machine learning in feature hilbert spaces
Maria Schuld and Nathan Killoran · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Later among the works it cites.
Cost-function-dependent barren plateaus in shallow quantum neural networks
M Cerezo, Akira Sone, Tyler Volkoff, Lukasz Cincio, and Patrick J Coles · 2020
Closest in time.
Trainability of dissipative perceptron-based quantum neural networks
Kunal Sharma, M Cerezo, Lukasz Cincio, and Patrick J Coles · 2020
Closest in time.
Noise-induced barren plateaus in variational quantum algorithms
Samson Wang, Enrico Fontana, M Cerezo, Kunal Sharma, Akira Sone, Lukasz Cincio, and Patrick J Coles · 2020
Closest in time.
Barren plateaus preclude learning scramblers
Zoë Holmes, Andrew Arrasmith, Bin Yan, Patrick J Coles, Andreas Albrecht, and Andrew T Sornborger · 2020
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Information scrambling and loschmidt echo
Bin Yan, Lukasz Cincio, and Wojciech H Zurek · 2020
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Key questions for the quantum machine learner to ask themselves
Nathan Wiebe · 2020
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