Quantum Machine Learning
101 papers for year 2019
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 97-101 of 101
Transfer learning in hybrid classical-quantum neural networks
Andrea Mari, Thomas R. Bromley, Josh Izaac, Maria Schuld, Nathan Killoran
2019
arXiv
arXiv preprint
Update of prior probabilities by minimal divergence
Jan Naudts
2019
arXiv
arXiv preprint
Variational Quantum Algorithms for Dimensionality Reduction and Classification
Jin-Min Liang, Shu-Qian Shen, Ming Li, Lei Li
2019
arXiv
arXiv preprint
Variational Quantum Circuits for Quantum State Tomography
Yong Liu, Dongyang Wang, Shichuan Xue, Anqi Huang, Xiang Fu, Xiaogang Qiang, Ping Xu, He-Liang Huang, Mingtang Deng, Chu Guo, Xuejun Yang, Junjie Wu
2019
arXiv
arXiv preprint
Yao.jl: Extensible, Efficient Framework for Quantum Algorithm Design
Xiu-Zhe Luo, Jin-Guo Liu, Pan Zhang, Lei Wang
2019
arXiv
arXiv preprint