Quantum Machine Learning
4,297 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 793-804 of 4,297
Machine Learning Approaches to Decoding Topological Quantum Codes
Changwon Lee, Tak Hur, Jeongwoo Jae, Daniel K. Park
Machine Learning based Optimization of CV-QKD Under Practical Constraints
Svitlana Matsenko, Amirhossein Ghazisaeidi, Marcin Jarzyna, Mateusz Kucharczyk, Mikkel Schmidt, Konrad Banaszek, Darko Zibar
Machine Learning Decoding of Circuit-Level Noise for Bivariate Bicycle Codes
John Blue, Harshil Avlani, Zhiyang He, Liu Ziyin, Isaac L. Chuang
Machine learning development for quantum computing and neutrino physics
Annalisa De Lorenzis
Machine learning for sample-based quantum diagonalization: generative configuration recovery and the classical-simulability frontier
Nicolás Bonilla Vargas
Machine Learning for Specialized QKD Aspects: A Survey of Adaptive Protocols, Free-Space Links, 6G Integration, and Steerability-Aware Security
Hasan Abbas Al-Mohammed, Afnan S. Al-Ali
Machine learning in applied microbiology, from data quality to model validation and implementation.
Barcan RA, Carradori S, Samsing F, Nguyen NL, He L, Wang Y, Barcan AS
Machine Learning of Quantum Entanglement from Noisy Measurements
Artur Czerwinski, Maciej Wiśniewski, Paweł Moszczyński
Machine Learning Optimal Quantum Error Correction Thresholds
Dominik Seip, Luis Colmenarez, Markus Schmitt, Markus Müller
Machine Learning Phonon Spectra for Fast and Accurate Optical Lineshapes of Defects.
Turiansky ME, Lyons JL, Bernstein N
Machine learning prediction of organic compound melting points informed by condensed-phase and electronic descriptors.
Mtetwa FT, Giles NF, Wilding WV, Knotts TA 4th
Machine learning prediction of the convergence criterion for a topological invariant of finite non-Hermitian chains
Raghav Chaturvedi, Viktor Könye, Ewelina M. Hankiewicz