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Image recognition is one of the primary applications of machine learning algorithms.
Density matrix formulation for quantum renormalization groups
Steven R. White · 1992
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Sergei Goreinov, Ivan Oseledets, D. Savostyanov, E. Tyrtyshnikov, and Nickolai Zamarashkin · 2010
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Patrick Rebentrost, Masoud Mohseni, and Seth Lloyd · 2014
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Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Warmstarting of model-based algorithm configuration
Marius Lindauer and Frank Hutter · 2018
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Barren plateaus in quantum neural network training landscapes
Jarrod R. McClean, Sergio Boixo, Vadim N. Smelyanskiy, Ryan Babbush, and Hartmut Neven · 2018
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Quantum annealing based optimization of robotic movement in manufacturing
Arpit Mehta, Murad Muradi, and Selam Woldetsadick · 2019
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Masayuki Ohzeki, Akira Miki, Masamichi J Miyama, and Masayoshi Terabe · 2019
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Michael Streif, Florian Neukart, and Martin Leib · 2019
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Quantum annealing applied to de-conflicting optimal trajectories for air traffic management
Tobias Stollenwerk, Bryan O’Gorman, Davide Venturelli, Salvatore Mandra, Olga Rodionova, Hokkwan Ng, Banavar Sridhar, Eleanor Gilbert Rieffel, and Rupak Biswas · 2019
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A hybrid solution method for the capacitated vehicle routing problem using a quantum annealer
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Frank Arute, Kunal Arya, Ryan Babbush, Dave Bacon, Joseph C Bardin, Rami Barends, Rupak Biswas, Sergio Boixo, Fernando GSL Brandao, David A Buell, et al · 2019
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Qdnn: Dnn with quantum neural network layers
Chen Zhao and Xiao-Shan Gao · 2019
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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
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Maria Schuld and Nathan Killoran · 2019
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Training the quantum approximate optimization algorithm without access to a quantum processing unit
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Layerwise learning for quantum neural networks
Andrea Skolik, Jarrod R McClean, Masoud Mohseni, Patrick van der Smagt, and Martin Leib · 2021
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Machine learning of high dimensional data on a noisy quantum processor
Evan Peters, Joao Caldeira, Alan Ho, Stefan Leichenauer, Masoud Mohseni, Hartmut Neven, Panagiotis Spentzouris, Doug Strain, and Gabriel N Perdue · 2021
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Variational quantum algorithms
Marco Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, et al · 2021
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Michael Streif and Martin Leib · 2020
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Hartree-fock on a superconducting qubit quantum computer
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Generation of high-resolution handwritten digits with an ion-trap quantum computer
Manuel S Rudolph, Ntwali Bashige Toussaint, Amara Katabarwa, Sonika Johri, Borja Peropadre, and Alejandro Perdomo-Ortiz · 2020
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Classical versus quantum models in machine learning: insights from a finance application
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Transfer learning in hybrid classical-quantum neural networks
Andrea Mari, Thomas R. Bromley, Josh Izaac, Maria Schuld, and Nathan Killoran · 2020
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Circuit-centric quantum classifiers
Maria Schuld, Alex Bocharov, Krysta M Svore, and Nathan Wiebe · 2020
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Sequential vs. integrated algorithm selection and configuration: A case study for the modular cma-es
Diederick Vermetten, Hao Wang, Carola Doerr, and Thomas Bäck · 2020
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An unsupervised feature learning for quantum-classical convolutional network with applications to fault detection
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On circuit-based hybrid quantum neural networks for remote sensing imagery classification
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A quantum-classical hybrid method for image classification and segmentation
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A rigorous and robust quantum speed-up in supervised machine learning
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Nonlinear tensor train format for deep neural network compression
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Matrix product states and projected entangled pair states: Concepts, symmetries, theorems
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Generalization in quantum machine learning from few training data
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Effect of data encoding on the expressive power of variational quantum-machine-learning models
Maria Schuld, Ryan Sweke, and Johannes Jakob Meyer · 2021
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Theory of overparametrization in quantum neural networks
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Supervised quantum machine learning models are kernel methods
Maria Schuld · 2021
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Quantum machine learning for radio astronomy
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Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning
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