Quantum Machine Learning
3,957 papers
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.
Showing 3781-3792 of 3,957
Characterization of decohering quantum systems: Machine learning approach
Markku P. V. Stenberg, Oliver Köhn, Frank K. Wilhelm
Corrigendum: Fault-tolerant quantum computation with a soft-decision decoder for error correction and detection by teleportation.
Goto H, Uchikawa H.
Decoherence control by quantum decoherence itself.
Roszak K, Filip R, Novotný T.
Designing High-Fidelity Single-Shot Three-Qubit Gates: A Machine Learning Approach
Ehsan Zahedinejad, Joydip Ghosh, Barry C. Sanders
Developing an Interactive Tutorial on a Mach-Zehnder Interferometer with Single Photons
Chandralekha Singh, Emily Marshman
Developing an Interactive Tutorial on a Quantum Eraser
Emily Marshman, Chandralekha Singh
Efficient synthesis of universal repeat-until-success quantum circuits.
Bocharov A, Roetteler M, Svore KM.
Entanglement discrimination in multi-rail electron-hole currents
J. P. Baltanás, D. Frustaglia
Experimental superposition of orders of quantum gates.
Procopio LM, Moqanaki A, Araújo M, Costa F, Alonso Calafell I, Dowd EG, Hamel DR, Rozema LA, Brukner Č, Walther P.
Fast machine-learning online optimization of ultra-cold-atom experiments
P. B. Wigley, P. J. Everitt, A. van den Hengel, J. W. Bastian, M. A. Sooriyabandara, G. D. McDonald, K. S. Hardman, C. D. Quinlivan, P. Manju, C. C. N. Kuhn, I. R. Petersen, A. Luiten, J. J. Hope, N. P. Robins, M. R. Hush
Hadronic deuteron polarizability contribution to the Lamb shift in muonic deuterium
A. V. Eskin, R. N. Faustov, A. P. Martynenko, F. A. Martynenko
Hybrid quantum gates between flying photon and diamond nitrogen-vacancy centers assisted by optical microcavities.
Wei HR, Long GL.