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 1-12 of 248
'Sawfish' Photonic Crystal Cavity for Near-Unity Emitter-to-Fiber Interfacing in Quantum Network Applications
Julian M. Bopp, Matthias Plock, Tim Turan, Gregor Pieplow, Sven Burger, Tim Schröder
$α$QBoost: An Iteratively Weighted Adiabatic Trained Classifier
Salvatore Certo, Andrew Vlasic, Daniel Beaulieu
3D Scalable Quantum Convolutional Neural Networks for Point Cloud Data Processing in Classification Applications
Hankyul Baek, Won Joon Yun, Joongheon Kim
A didactic approach to quantum machine learning with a single qubit
Elena Peña Tapia, Giannicola Scarpa, Alejandro Pozas-Kerstjens
A distribution testing oracle separation between QMA and QCMA
Anand Natarajan, Chinmay Nirkhe
A duplication-free quantum neural network for universal approximation
Xiaokai Hou, Guanyu Zhou, Qingyu Li, Shan Jin, Xiaoting Wang
A hierarchical approach for building distributed quantum systems.
Davarzani Z, Zomorodi M, Houshmand M.
A kernel-based quantum random forest for improved classification
Maiyuren Srikumar, Charles D. Hill, Lloyd C. L. Hollenberg
A Multicomponent Nucleic Acid Enzyme-Cleavable Quantum Dot Nanobeacon for Highly Sensitive Diagnosis of Tuberculosis with the Naked Eye
Ou Hu, Zeyu Li, Jinghao Wu, Yaoju Tan, Zuanguang Chen, Yanli Tong
A Needs Analysis Study in Developing Quantum Physics Instructional Module for Secondary School With an Integrated Stem Education Approach
Laurah Markus
A needs analysis study in developing quantum physics instructional module for secondary school with an integrated stem education approach
Laurah Markus
A Note on Quantum Divide and Conquer for Minimal String Rotation
Qisheng Wang