Quantum Machine Learning

237 papers for year 2020

Quantum Machine Learning Research Context

This category covers quantum machine learning research, including quantum kernels, variational classifiers, hybrid learning systems, generative models, and QML benchmarks.

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All sources 237 arXiv preprints 196 Crossref 22 Europe PMC 12 DOAJ 7

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Showing 121-132 of 237

Performance vs. Spectral Properties For Single-Sideband Continuous Phase Modulation

Karim Kassan, Haïfa Farès, D. Christian Glattli, Yves Louët

2020 arXiv arXiv preprint

Photonic band structure design using persistent homology

Daniel Leykam, Dimitris G Angelakis

2020 arXiv arXiv preprint

Picking Efficient Portfolios from 3,171 US Common Stocks with New Quantum and Classical Solvers

Jeffrey Cohen, Clark Alexander

2020 arXiv arXiv preprint

Polyadic Quantum Classifier

William Cappelletti, Rebecca Erbanni, Joaquín Keller

2020 arXiv arXiv preprint

Portfolio Optimisation Using the D-Wave Quantum Annealer

Frank Phillipson, Harshil Singh Bhatia

2020 arXiv arXiv preprint

Portfolio Optimization of 60 Stocks Using Classical and Quantum Algorithms

Jeffrey Cohen, Alex Khan, Clark Alexander

2020 arXiv arXiv preprint

Potassium-Induced Passivation of Deep Traps in Bismuth-Doped Hybrid Lead Bromide Perovskite Nanocrystals: Massive Amplification of Photoluminescence Quantum Yield

Shovon Chatterjee, Mainak Ghosal, Khushubo Tiwari, Pratik Sen

2020 Crossref The Journal of Physical Chemistry Letters

Power of data in quantum machine learning

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

2020 arXiv arXiv preprint

Practical application improvement to Quantum SVM: theory to practice

Jae-Eun Park, Brian Quanz, Steve Wood, Heather Higgins, Ray Harishankar

2020 arXiv arXiv preprint

Predicting impurity spectral functions using machine learning

Erica J. Sturm, Matthew R. Carbone, Deyu Lu, Andreas Weichselbaum, Robert M. Konik

2020 arXiv arXiv preprint

Predicting toxicity by quantum machine learning

Teppei Suzuki, Michio Katouda

2020 arXiv arXiv preprint

Programmable Quantum Annealers as Noisy Gibbs Samplers

Marc Vuffray, Carleton Coffrin, Yaroslav A. Kharkov, Andrey Y. Lokhov

2020 arXiv arXiv preprint

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