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 37-48 of 290
Hybrid quantum classical framework for electroencephalogram driven neurological processing in epileptic seizure taxonomy.
Padmaja B, Maram B, Raheem AKA, Khan S, Basheti I, Abass KS, Khan WA.
Hybrid Quantum-Classical Algorithm for Robust Optimization via Stochastic-Gradient Online Learning.
Lim D, Doriguello JF, Rebentrost P.
Large-Scale Efficient Molecule Geometry Optimization with Hybrid Quantum-Classical Computing.
Hao Y, Ding Q, Wang X, Yuan X.
Learning to Build Quantum Kernels: A Reinforcement Learning Framework for Quantum SVC Optimization
Barbato L, Buonaiuto G, Marassi L, Marrone S, Sansone C, Esposito M, Gargiulo F.
Light cone cancellation for variational quantum eigensolver in solving noisy Max-Cut.
Lee X, Yan X, Xie N, Saito Y, Kurosawa L, Asai N, Cai D, Lau HC.
Light-Weight Quantum Binary Image Classifier
Nagy M.
Local surrogates for quantum machine learning
Nair SR, Ferrie C.
Memory as Spatiotemporal Delay: A Unified Hybrid Framework for Quantum-cosmic Energetics and Astrobiological Dynamics
Tosunoğlu HH, Demir T, Karenzo A, Shah NA.
Modeling and benchmarking quantum optical neurons for efficient neural computation.
Andrisani A, Vessio G, Sgobba F, Di Lena F, Santamaria LA, Castellano G.
Molecular Resonance Identification in Complex Absorbing Potentials via Integrated Quantum Computing and High-Throughput Computing.
Dai J, Vidwans A, Wan EH, Miller AX, Soley MB.
MolGAN-QRL: a hybrid framework for molecule generation using quantum-enhanced reinforcement learning.
Hergli MI, Harigua-Souiai E.
Network separation modeling and quantum computing for developing wildfire fuelbreak strategy.
Dent S, Stoddard K, Smith M, Strelzoff A, Cummings C, Cegan J, Linkov I.