Quantum Machine Learning
416 papers for year 2023
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 25-36 of 416
A pragma based C++ framework for hybrid quantum/classical computation
Arnaud Gazda, Oceane Koska
A proposal to characterize and quantify superoscillations
Yu Li, José Polo-Gómez, Eduardo Martín-Martínez
A Quadratic Sample Complexity Reduction for Agnostic Learning via Quantum Algorithms
Daniel Z. Zanger
A Quantum Federated Learning Framework for Classical Clients
Yanqi Song, Yusen Wu, Shengyao Wu, Dandan Li, Qiaoyan Wen, Sujuan Qin, Fei Gao
A quantum moving target segmentation algorithm for grayscale video
Wenjie Liu, Lu Wang, Qingshan Wu
A quantum segmentation algorithm based on local adaptive threshold for NEQR image
Lu Wang, Wenjie Liu
A quantum tug of war between randomness and symmetries on homogeneous spaces
Rahul Arvind, Kishor Bharti, Jun Yong Khoo, Dax Enshan Koh, Jian Feng Kong
A Review of the Applications of Quantum Machine Learning in Optical Communication Systems
Ark Modi, Alonso Viladomat Jasso, Roberto Ferrara, Christian Deppe, Janis Noetzel, Fred Fung, Maximilian Schaedler
A sublinear time quantum algorithm for longest common substring problem between run-length encoded strings
Tzu-Ching Lee, Han-Hsuan Lin
A Survey of Classical And Quantum Sequence Models
I-Chi Chen, Harshdeep Singh, V L Anukruti, Brian Quanz, Kavitha Yogaraj
A Survey of Machine Learning Assisted Continuous-Variable Quantum Key Distribution
Nathan K. Long, Robert Malaney, Kenneth J. Grant
A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead
Kamila Zaman, Alberto Marchisio, Muhammad Abdullah Hanif, Muhammad Shafique