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 3469-3480 of 3,957
Ultimate Limits of Thermal Pattern Recognition
Cillian Harney, Leonardo Banchi, Stefano Pirandola
Unboxing Quantum Black Box Models: Learning Non-Markovian Dynamics
Stefan Krastanov, Kade Head-Marsden, Sisi Zhou, Steven T. Flammia, Liang Jiang, Prineha Narang
Unifying Aspects of Generalized Calculus
Marek Czachor
Universal Approximation Property of Quantum Machine Learning Models in Quantum-Enhanced Feature Spaces
Takahiro Goto, Quoc Hoan Tran, Kohei Nakajima
Universal non-Markovianity detection in hybrid open quantum systems.
Svozilík J, Hidalgo-Sacoto R, Arkhipov II.
Usefulness of adaptive strategies in asymptotic quantum channel discrimination
Farzin Salek, Masahito Hayashi, Andreas Winter
Utilizing a Fully Optical and Reconfigurable PUF as a Quantum Authentication Mechanism
H S. Jacinto, A. Matthew Smith
Variational approximation for two-dimensional quantum droplets
Sherzod R. Otajonov, Eduard N. Tsoy, Fatkhulla Kh. Abdullaev
Variational Quantum Cloning: Improving Practicality for Quantum Cryptanalysis
Brian Coyle, Mina Doosti, Elham Kashefi, Niraj Kumar
Vector computation
Karl Svozil
VSQL: Variational Shadow Quantum Learning for Classification
Guangxi Li, Zhixin Song, Xin Wang
What is Quantum Computing and How it Works
Adjunct Professor, Golden Gate University, Ageno School of Business, Data Analytic, San Francisco, California, USA, Bahman Zohuri, Farhang Mossavar Rahmani, Professor of Finance and Director of MBA School of Business and Management, National University, San Diego, California, USA