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Variational Quantum Algorithms

Dec 16, 2020
M. Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C. Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R. McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, Patrick J. Coles

* Review Article. 29 pages, 6 figures 

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Power of data in quantum machine learning

Nov 03, 2020
Hsin-Yuan Huang, Michael Broughton, Masoud Mohseni, Ryan Babbush, Sergio Boixo, Hartmut Neven, Jarrod R. McClean

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Learning to learn with quantum neural networks via classical neural networks

Jul 11, 2019
Guillaume Verdon, Michael Broughton, Jarrod R. McClean, Kevin J. Sung, Ryan Babbush, Zhang Jiang, Hartmut Neven, Masoud Mohseni

* 12 pages, 4 figures 

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Barren plateaus in quantum neural network training landscapes

Mar 29, 2018
Jarrod R. McClean, Sergio Boixo, Vadim N. Smelyanskiy, Ryan Babbush, Hartmut Neven

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Bayesian Network Structure Learning Using Quantum Annealing

Oct 02, 2014
Bryan O'Gorman, Alejandro Perdomo-Ortiz, Ryan Babbush, Alan Aspuru-Guzik, Vadim Smelyanskiy

* Eur. Phys. J. Spec. Top., 225 (1), 163 (2015) 

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Construction of non-convex polynomial loss functions for training a binary classifier with quantum annealing

Jun 17, 2014
Ryan Babbush, Vasil Denchev, Nan Ding, Sergei Isakov, Hartmut Neven

* 15 pages, 6 figures 

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