Quantum Machine Learning
290 papers from Europe PMC
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 181-192 of 290
Experimental semi-autonomous eigensolver using reinforcement learning.
Pan CY, Hao M, Barraza N, Solano E, Albarrán-Arriagada F.
Exponential suppression of bit or phase errors with cyclic error correction.
Google Quantum AI.
Hamiltonian simulation algorithms for near-term quantum hardware.
Clinton L, Bausch J, Cubitt T.
Importance of Kernel Bandwidth in Quantum Machine Learning
Shaydulin R, Wild S.
Iterative qubit-excitation based variational quantum eigensolver
Yordanov Y, Armaos V, Barnes C, Arvidsson-Shukur D.
Learning Temporal Quantum Tomography.
Tran QH, Nakajima K.
Optimization of Sources of Circulating Cell-Free DNA Variability for Downstream Molecular Analysis.
Till JE, Black TA, Gentile C, Abdalla A, Wang Z, Sangha HK, Roth JJ, Sussman R, Yee SS, O'Hara MH, Thompson JC, Aggarwal C, Hwang WT, Elenitoba-Johnson KSJ, Carpenter EL.
Quantum deep reinforcement learning for clinical decision support in oncology: application to adaptive radiotherapy.
Niraula D, Jamaluddin J, Matuszak MM, Haken RKT, Naqa IE.
Resonant quantum principal component analysis.
Li Z, Chai Z, Guo Y, Ji W, Wang M, Shi F, Wang Y, Lloyd S, Du J.
Robust and fast post-processing of single-shot spin qubit detection events with a neural network.
Struck T, Lindner J, Hollmann A, Schauer F, Schmidbauer A, Bougeard D, Schreiber LR.
Variational Quantum Chemistry Programs in JaqalPaq.
Maupin OG, Baczewski AD, Love PJ, Landahl AJ.
A heterometallic [LnLn'Ln] lanthanide complex as a qubit with embedded quantum error correction.
Macaluso E, Rubín M, Aguilà D, Chiesa A, Barrios LA, Martínez JI, Alonso PJ, Roubeau O, Luis F, Aromí G, Carretta S.