Quantum Machine Learning
86 papers from DOAJ
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 61-72 of 86
On the Development of the Scientific Base of Quantum Technologies
A. I. Terekhov
Scattering-Assisted Computational Imaging
Yiwei Sun, Xiaoyan Wu, Jianhong Shi, Guihua Zeng
The Feasibility of the CRYSTALS-Kyber Scheme for Smart Metering Systems
Vinicius L. R. Da Costa, Andrei Camponogara, Julio Lopez, Moises V. Ribeiro
Three-dimensional natural color imaging based on focus level correlation algorithm using structured illumination microscopy
Mengrui Wang, Mengrui Wang, Tianyu Zhao, Zhaojun Wang, Kun Feng, Jingrong Ren, Yansheng Liang, Shaowei Wang, Ming Lei
Trie-based ranking of quantum many-body states
Markus Wallerberger, Karsten Held
Assessment of image generation by quantum annealer
Takehito Sato, Masayuki Ohzeki, Kazuyuki Tanaka
Improving PV Resilience by Dynamic Reconfiguration in Distribution Grids: Problem Complexity and Computation Requirements
Filipe F. C. Silva, Pedro M. S. Carvalho, Luís A. F. M. Ferreira
Level by level image compression-encryption algorithm based on quantum chaos map
Ranjeet Kumar Singh, Binod Kumar, Dilip Kumar Shaw, Danish Ali Khan
Part‐level attention networks for cross‐domain person re‐identification
Qun Zhao, Nisuo Du, Zhi Ouyang, Ning Kang, Ziyan Liu, Xu Wang, Qing He, Yiling Xu, Shichun Ge, Jingkuan Song
Speeding up quantum dissipative dynamics of open systems with kernel methods
Arif Ullah, Pavlo O. Dral
Detecting outliers in segmented genomes of flu virus using an alignment-free approach
Mosaab Daoud
Expressibility and trainability of parametrized analog quantum systems for machine learning applications
Jirawat Tangpanitanon, Supanut Thanasilp, Ninnat Dangniam, Marc-Antoine Lemonde, Dimitris G. Angelakis