Quantum Machine Learning
24 papers for year 2025 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 1-12 of 24
A low-circuit-depth quantum computing approach to the nuclear shell model
Stevenson P, Sarma C.
A quantum machine learning-based predictive analysis of CERN collision events.
Tripathi S, Upadhyay H, Soni J.
Advanced Quantum Machine Learning Framework Enhances Classification Accuracy by 34% Through Multi-Dimensional Geometric Optimization
Chaplart TB.
An integrated optical hardware for realization of quantum error correction operators.
Armaghani S, Rostami A.
Artificial intelligence in financial market prediction: advancements in machine learning for stock price forecasting.
Rohan A, Hossen MD, Pranto MN, Hossain B, Yoshi AM, Islam R.
Can Entanglement Measures Predict LOCC Majorization Ordering? A Machine Learning Study of Two-Qubit Systems
Erol V.
How does Quantum Machine Learning (QML) improve optimization in complex systems compared to classical machine learning algorithms?
Pise S.
Hybrid quantum neural network models for fruit quality assessment.
Khairi DU, Ahsan K, Ali SZ, Alhalabi W, Albaradei S, Anwar MS.
Learning to decode logical circuits.
Zhou Y, Wan C, Xu Y, Zhou JP, Weinberger KQ, Kim EA.
Local clustering decoder as a fast and adaptive hardware decoder for the surface code.
Ziad AB, Zalawadiya A, Topal C, Camps J, Gehér GP, Stafford MP, Turner ML.
Machine-Learning-Assisted Parameterization of Quantum Walk Algorithms
Ghayour P.
Metropolitan-scale ion-photon entanglement via a quantum network node with hybrid multiplexing enhancements.
Cui ZB, Wang ZQ, Lai PC, Wang Y, Shi JX, Liu PY, Sun YD, Tian ZC, Liang YB, Qi BX, Huang YY, Zhou ZC, Wu YK, Xu Y, Duan LM, Pu YF.