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 2329-2340 of 4,297
Hybrid Classical-Quantum architecture for vectorised image classification of hand-written sketches
Y. Cordero, S. Biswas, F. Vilariño, M. Bilkis
Hybrid data-driven and physics-based modeling for viscosity prediction of ionic liquids
Jing Fan, Zhengxing Dai, Jian Cao, Liwen Mu, Xiaoyan Ji, Xiaohua Lu
Hybrid Heuristic Algorithms for Adiabatic Quantum Machine Learning Models
Bahram Alidaee, Haibo Wang, Lutfu Sua, Wade Liu
Hybrid model of the kernel method for quantum computers
Jhordan Silveira de Borba, Jonas Maziero
Hybrid quantum enhanced federated learning for cyber attack detection
G. Subramanian, M. Chinnadurai
Hybrid quantum-classical approach for combinatorial problems at hadron colliders
Jacob L. Scott, Zhongtian Dong, Taejoon Kim, Kyoungchul Kong, Myeonghun Park
Hybrid Quantum-Classical Convolutional Neural Networks for Image Classification in Multiple Color Spaces
Kwok-Ho Ng, Tingting Song, Zhiquan Liu
Hybrid Quantum-Classical Feature Extraction approach for Image Classification using Autoencoders and Quantum SVMs
Donovan Slabbert, Francesco Petruccione
Hybrid Quantum-Classical Machine Learning with String Diagrams
Alexander Koziell-Pipe, Aleks Kissinger
Hybrid Quantum-Classical Reinforcement Learning in Latent Observation Spaces
Dániel T. R. Nagy, Csaba Czabán, Bence Bakó, Péter Hága, Zsófia Kallus, Zoltán Zimborás
Hyperdimensional Quantum Factorization
Prathyush Poduval, Zhuowen Zou, Alvaro Velasquez, Mohsen Imani
Identifying the determining factors of detonation properties for linear nitroaliphatics with high-throughput computation and machine learning
Wen Qian, Jing Huang, Shi-tai Guo, Bo-wen Duan, Wei-yu Xie, Jian Liu, Chao-yang Zhang