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 817-828 of 4,297
Machine learning-driven molecular engineering of nucleic acids.
Shi Q, Lv H, Wang F, Fan C, Li M
Machine learning-driven spectral decomposition and pattern recognition for carbon quantum dot fluorescence sensing: From quantum confinement to multi-analyte detection
Biju Theruvil Sayed, Zyad Shaaban, Maharshikumar B. Shukla, Sumit Sharma, Ozodbek Nematov, Ibrokhim Sapaev, M.K. Sharma, Aseel Smerat, Ahmad khayyat, Ahmad Mohebi
Machine learning-driven surface and interface engineering in perovskite quantum dots for photoluminescence-based and chemical sensing platforms
Ghaleb Oriquat, Kwthr Hafdh Jbar, Omayma Salim Waleed, Manoj A. Vora, Roopashree R, Lalita Chopra, Sadridin Eshkaraev, Dushamov Dilshod Azadovich, Hadi Nooriadeh
Machine Learning-Enabled In Situ Diagnostics for Intelligent Plasma-Based Semiconductor Manufacturing: A Review.
Kang M, Kim S, Go E, Byun S, Cho D, Kim T, Kang H, Lee J, Ko M, Jeon N, Choi MS, Kim HU
Machine Learning‐Based Discovery of Natural PknB Inhibitors Against Drug‐Resistant <i>Mycobacterium tuberculosis</i> With Multi‐Scale Modeling and Quantum Mechanical Validation
Rahul Singh, Vishwas Tripathi, Vivek Dhar Dwivedi, Garima Chouhan
Machine Learning–Enhanced Quantum–Classical Benders Decomposition for Stochastic Unit Commitment
Reza Mahroo, Amin Kargarian
Machine learning–guided thermal stability and degradation kinetics of ultra-fine polyamide-derived carbon quantum dots
Christian Ebere Enyoh, Qingyue Wang
Machine Learning/Molecular Mechanics Enzymology for the Next Generation of Computational Enzymatic Catalysis.
Wang X, Wang J, Li WL
Machine-learned, finite temperature Fermi-operator expansions suitable for GPUs and AI-hardware
Stanislaw Kowalski, Christian F. A. Negre, Anders M. N. Niklasson, Kipton Barros, Joshua Finkelstein
Machine-Learning Optimization and Characterization of a High-Optical-Depth Two-Color Nanofiber Trap
W. Crump, M. Sadeghi, M. D. Hoogerland
Machine-learning-assisted material and geometry characterization from Casimir force measurement
Hideo Iizuka, Shanhui Fan
Machine-Learning-Empowered Quantum Sensing of the Plaquette Phase in a Three-Level Delta System
Lorenzo Vitale, Shreyasi Mukherjee, Dario Fasone, Enrico Martello, Elisabetta Paladino, Luigi Giannelli, Giuseppe Falci