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 2533-2544 of 3,957
New circuits and an open source decoder for the color code
Craig Gidney, Cody Jones
Non-asymptotic Approximation Error Bounds of Parameterized Quantum Circuits
Zhan Yu, Qiuhao Chen, Yuling Jiao, Yinan Li, Xiliang Lu, Xin Wang, Jerry Zhijian Yang
Non-Linear Transformations of Quantum Amplitudes: Exponential Improvement, Generalization, and Applications
Arthur G. Rattew, Patrick Rebentrost
Non-Markovian cost function for quantum error mitigation with Dirac Gamma matrices representation.
Ahn D.
Nuclear Physics Opportunities at European Small-Scale Facilities
Jelena Vesić, Matjaž Vencelj
On fundamental aspects of quantum extreme learning machines
Weijie Xiong, Giorgio Facelli, Mehrad Sahebi, Owen Agnel, Thiparat Chotibut, Supanut Thanasilp, Zoë Holmes
On Neural Quantum Support Vector Machines
Lars Simon, Manuel Radons
On the Applicability of Quantum Machine Learning
Sebastian Raubitzek, Kevin Mallinger
On the connection between least squares, regularization, and classical shadows
Zhihui Zhu, Joseph M. Lukens, Brian T. Kirby
On the expressivity of embedding quantum kernels
Elies Gil-Fuster, Jens Eisert, Vedran Dunjko
On the rank of two-dimensional simplicial distributions
Cihan Okay
One nine availability of a Photonic Quantum Computer on the Cloud toward HPC integration
Nicolas Maring, Andreas Fyrillas, Mathias Pont, Edouard Ivanov, Eric Bertasi, Mario Valdivia, Jean Senellart