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 49-60 of 290
Noisy Qubits, Hard Problems: A SystematicReview and Taxonomy of Quantum OptimizationBeyond Toy Benchmarks
Sridhara SK, Kumar KK.
NQ-SVM: Scalable Quantum Kernel Learning via Nyström-Based Support Vector Machines
Do DT, Thudumu S, Jayaraman PP, Nguyen DT.
On the fundamental resource for exponential advantage in quantum channel learning.
Kim M, Oh C.
Optimal Complexity of Parameterized Quantum Circuits.
Correr GI, Azado PC, Soares-Pinto DO, Carlo GG.
Parametrized Quantum Circuit Learning for Quantum Chemical Applications.
Jones GM, Prasad VK, Fekl U, Jacobsen HA.
Performance Analysis of NIST Standardized Post-Quantum Cryptography Algorithms in Resource-Constrained IoT Environments
Toufik DM, Khaiat SB.
Polynomially efficient quantum enabled variational Monte Carlo for training neural-network quantum states for physico-chemical applications
Sajjan M, Singh V, Kais S.
Post-Quantum Link-based Ring Signature Model and Artificial Bee Colony (ABC) Algorithm for Effective Data Management in IoT-based Smart Cities
Shaker AA, Abduljabbar Rashid S, Al Mashhadany Y.
Power and Limitations of Distributed Quantum State Purification.
Zhao B, Chen YA, Zhao X, Zhu C, Chiribella G, Wang X.
Pretreatment Radiation Esophagitis Prediction using Quantum Machine Learning in Esophageal Cancer Patients.
Xie C, Shen Y, He J, Guo M, Mu Y, Li L, Wang W, Dou M, Zhou Y, Zhang J, Ai Y, Jin X.
Prototype-Based Classifiers and Vector Quantization on a Quantum Computer-Implementing Integer Arithmetic Oracles for Nearest Prototype Search.
Engelsberger A, Pšeničkova M, Villmann T.
QRadX-KOA: A RadImageNet Driven Quantum Transfer Learning Framework for Kellgren–Lawrence Grading of Knee Osteoarthritis
P HGV, S N.