Quantum Machine Learning
248 papers for year 2022
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 241-248 of 248
Understanding and eliminating spurious modes in variational Monte Carlo using collective variables
Huan Zhang, Robert J. Webber, Michael Lindsey, Timothy C. Berkelbach, Jonathan Weare
2022
arXiv
arXiv preprint
Understanding the Mapping of Encode Data Through An Implementation of Quantum Topological Analysis
Andrew Vlasic, Anh Pham
2022
arXiv
arXiv preprint
Universal adversarial examples and perturbations for quantum classifiers.
Gong W, Deng DL
2022
PubMed
National science review
Utilizing quantum genetic algorithm with TM to solve DEs
Ahmed Hamid Elias, Igor Klebanov, Salah A. Albermany
2022
Crossref
Periodicals of Engineering and Natural Sciences (PEN)
Variational Quantum Algorithms for Chemical Simulation and Drug Discovery
Hasan Mustafa, Sai Nandan Morapakula, Prateek Jain, Srinjoy Ganguly
2022
arXiv
arXiv preprint
Variational Quantum Kernels with Task-Specific Quantum Metric Learning
Daniel T. Chang
2022
arXiv
arXiv preprint
Variational quantum one-class classifier
Gunhee Park, Joonsuk Huh, Daniel K. Park
2022
arXiv
arXiv preprint
ViSNet: an equivariant geometry-enhanced graph neural network with vector-scalar interactive message passing for molecules
Yusong Wang, Shaoning Li, Xinheng He, Mingyu Li, Zun Wang, Nanning Zheng, Bin Shao, Tie-Yan Liu, Tong Wang
2022
arXiv
arXiv preprint