Quantum Machine Learning
3,957 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 2221-2232 of 3,957
Red-QAOA: Efficient Variational Optimization through Circuit Reduction
Meng Wang, Bo Fang, Ang Li, Prashant Nair
Redefining Lexicographical Ordering: Optimizing Pauli String Decompositions for Quantum Compiling
Qunsheng Huang, David Winderl, Arianne Meijer-van de Griend, Richie Yeung
Reexamination of the realtime protection for user privacy in practical quantum private query
Chun-Yan Wei, Xiao-Qiu Cai, Tian-Yin Wang
Regression of Concurrence via Local Unitary Invariants.
Li M, Wang W, Zhang X, Wang J, Li L, Shen S.
Regressions on quantum neural networks at maximal expressivity.
Panadero I, Ban Y, Espinós H, Puebla R, Casanova J, Torrontegui E.
Reinforcement learning with learned gadgets to tackle hard quantum problems on real hardware
Akash Kundu, Leopoldo Sarra
Reinforcement learning-based architecture search for quantum machine learning
Frederic Rapp, David A. Kreplin, Marco F. Huber, Marco Roth
Representing arbitrary ground states of toric code by a restricted Boltzmann machine
Penghua Chen, Bowen Yan, Shawn X. Cui
Residue Number System (RNS) based Distributed Quantum Addition
Bhaskar Gaur, Travis S. Humble, Himanshu Thapliyal
Resolvability of classical-quantum channels
Masahito Hayashi, Hao-Chung Cheng, Li Gao
Resolvent-based quantum phase estimation: Towards estimation of parametrized eigenvalues
Abhijeet Alase, Salini Karuvade
Reverse Map Projections as Equivariant Quantum Embeddings
Max Arnott, Dimitri Papaioannou, Kieran McDowall, Phalgun Lolur, Bambordé Baldé