Quantum Machine Learning
4,009 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 1021-1032 of 4,009
Quantum principal component analysis without eigenvector recovery
Yewei Yuan, Michele Minervini, Mark M. Wilde, Nana Liu
Quantum Proper Scoring Rules: Minimax Estimation and Resource-Theoretic Advantages
M. W. AlMasri
Quantum Property Testing for Bounded-Degree Directed Graphs
Pan Peng, Jingyu Wu
Quantum Random Features: A Spectral Framework for Quantum Machine Learning
Akitada Sakurai, Aoi Hayashi, William John Munro, Kae Nemoto
Quantum Random Forest for the Regression Problem
Kamil Khadiev, Liliya Safina
Quantum Recurrent Unit: A Parameter-Efficient Quantum Neural Network Architecture for NISQ Devices
Tzong-Daw Wu, Hsi-Sheng Goan
Quantum reinforcement learning for dynamic multi-objective energy management in community microgrids
Yan Gu, Huiru Yan, Qingle Wang, Cong Liu, Cheng Liu, Long Cheng
Quantum Reinforcement Learning-Guided Diffusion Model for Image Synthesis via Hybrid Quantum-Classical Generative Model Architectures
Chi-Sheng Chen, En-Jui Kuo
Quantum Reservoir Autoencoder for Blind Decryption: Two-Phase Protocol and Noise Resilience
Hikaru Wakaura, Taiki Tanimae
Quantum Reservoir Computing for Short-Term Power Load Forecasting in Resource-Constrained Energy Systems
Mansi Od, Param Pathak, Nouhaila Innan, Muhammad Shafique
Quantum reservoir computing induced by controllable damping
Emanuele Ricci, Francesco Monzani, Luca Nigro, Enrico Prati
Quantum ring all-reduce: communication and privacy advantages for distributed learning
María Gragera Garcés, Lirandë Pira