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 169-180 of 4,297
Antenna Array Beamforming Based on a Hybrid Quantum Optimization Framework
Shuai Zeng
Applicability and Limitations of Quantum Circuit Cutting in Classical State-Vector Simulation
Mitsuhiro Matsumoto, Shinichiro Sanji, Takahiko Satoh
Application and optimization of quantum-powered generative models for job shop scheduling in semiconductor manufacturing
Truong Ngoc Cuong, Sam-Sang You, Hwan-Seong Kim, Le Ngoc Bao Long, Duy Anh Nguyen, Nguyen Duy Tan
Application of a Quantum Amplitude Redistribution Algorithm to the Data Filtering Problem
Karina Zakharova, Artem Chernikov, Sergey Sysoev
Applications of classical and quantum machine learning in manufacturing: predictive maintenance, scheduling and tribology
Abdullah Jawad, Ethan Stefan-Henningsen, Amirkianoosh Kiani
Applications, Progress, and Challenges of Surfactants in Chemical Mechanical Polishing for Copper Interconnects.
Wang M, Niu X, Zhou J, Hu B, Li J, Wu Z, Liu Z, Ma Q, Song S, Jia Y
Approximate Adders with Configurable Input Wiring: A Quantum-dot Cellular Automata Nanocomputing Perspective
Angshuman Khan, Naeem Maroof, M. C. Parameshwara
AQ-Stacker: An Adaptive Quantum Matrix Multiplication Algorithm with Scaling via Parallel Hadamard Stacking
Wladimir Silva
Aqueous Continuous Flow Synthesis of Cadmium Chalcogenide Quantum Dots: Opportunities and Challenges.
Campalani C, Petit G, Monbaliu JM
Arithmetic-Aware Quantum Neural Networks Using Fault-Tolerant BCD-Excess-3 Encoding
Sandip Das
Artificial Intelligence and its Current Role in Clinical Outcome Prediction, Musculoskeletal Imaging, and Economic and Ethical Considerations within Orthopedics and Sports Medicine.
O'Malley E, Soth B, Capitano A, Bensa A, Eskew J, Dancy M, Nwachukwu B
Artificial intelligence in drug discovery from advanced molecular representation to pipeline applications.
Zhou X, Tao W