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 3613-3624 of 3,957
Further Limitations on Information-Theoretically Secure Quantum Homomorphic Encryption
Michael Newman
General modeling framework for quantum photodetectors
Steve M. Young, Mohan Sarovar, François Léonard
Generalization of the output of variational quantum eigensolver by parameter interpolation with low-depth ansatz
Kosuke Mitarai, Tennin Yan, Keisuke Fujii
Generative model benchmarks for superconducting qubits
Kathleen E. Hamilton, Eugene F. Dumitrescu, Raphael C. Pooser
Hardening quantum machine learning against adversaries
Nathan Wiebe, Ram Shankar Siva Kumar
High-dimensional quantum encoding via photon-subtracted squeezed states
Francesco Arzani, Alessandro Ferraro, Valentina Parigi
Implementation of an efficient linear-optical quantum router.
Bartkiewicz K, Černoch A, Lemr K.
Improved Quantum Multicollision-Finding Algorithm
Akinori Hosoyamada, Yu Sasaki, Seiichiro Tani, Keita Xagawa
Improvement of optical image by measurement reduction technique at parametric multiplexing
D. A. Balakin, A. S. Chirkin
Learning Robust and High-Precision Quantum Controls
Re-Bing Wu, Haijin Ding, Daoyi Dong, Xiaoting Wang
Logical structures underlying quantum computing
Federico Holik, Giuseppe Sergioli, Hector Freytes, Angelo Plastino
Machine Learning for Optimal Parameter Prediction in Quantum Key Distribution
Wenyuan Wang, Hoi-Kwong Lo