Quantum Machine Learning
248 papers for year 2022
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 145-156 of 248
Possibilistic simulation of quantum circuits by classical circuits
Daochen Wang
Post-Quantum Cryptography
Jose Pinto
Post-reconstruction attenuation correction for SPECT myocardium perfusion imaging facilitated by deep learning-based attenuation map generation.
Liu H, Wu J, Shi L, Liu Y, Miller E, Sinusas A, Liu YH, Liu C
PQLM -- Multilingual Decentralized Portable Quantum Language Model for Privacy Protection
Shuyue Stella Li, Xiangyu Zhang, Shu Zhou, Hongchao Shu, Ruixing Liang, Hexin Liu, Leibny Paola Garcia
Predicting Good Quantum Circuit Compilation Options
Nils Quetschlich, Lukas Burgholzer, Robert Wille
Prediction of chemical shift in NMR: A review.
Jonas E, Kuhn S, Schlörer N
Presence and Absence of Barren Plateaus in Tensor-Network Based Machine Learning
Zidu Liu, Li-Wei Yu, L.-M. Duan, Dong-Ling Deng
Projection Valued Measure-based Quantum Machine Learning for Multi-Class Classification
Won Joon Yun, Hankyul Baek, Joongheon Kim
Promoting the transition to quantum thinking: development of a secondary school course for addressing knowledge revision, organization, and epistemological challenges
Giacomo Zuccarini, Marisa Michelini
Protocols for classically training quantum generative models on probability distributions
Sachin Kasture, Oleksandr Kyriienko, Vincent E. Elfving
Pulse-efficient quantum machine learning
André Melo, Nathan Earnest-Noble, Francesco Tacchino
Q2Graph: a modelling tool for measurement-based quantum computing
Greg Bowen, Simon Devitt