Quantum Machine Learning
4,297 papers
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 2569-2580 of 4,297
Residue Number System (RNS) based Distributed Quantum Addition
Bhaskar Gaur, Travis S. Humble, Himanshu Thapliyal
Resolvability of classical-quantum channels
Masahito Hayashi, Hao-Chung Cheng, Li Gao
Resolvent-based quantum phase estimation: Towards estimation of parametrized eigenvalues
Abhijeet Alase, Salini Karuvade
Reverse Map Projections as Equivariant Quantum Embeddings
Max Arnott, Dimitri Papaioannou, Kieran McDowall, Phalgun Lolur, Bambordé Baldé
Review on 6G communication and its architecture, technologies included, challenges, security challenges and requirements, applications, with respect to AI domain
Pranita Bhide, Dhanush Shetty, Suresh Mikkili
Rise and Fall of Anderson Localization by Lattice Vibrations: A Time-Dependent Machine Learning Approach
Yoel Zimmermann, Joonas Keski-Rahkonen, Anton M. Graf, Eric J. Heller
Rise of conditionally clean ancillae for efficient quantum circuit constructions
Tanuj Khattar, Craig Gidney
RobQuNNs: A Methodology for Robust Quanvolutional Neural Networks against Adversarial Attacks
Walid El Maouaki, Alberto Marchisio, Taoufik Said, Muhammad Shafique, Mohamed Bennai
Robust and optimal loading of general classical data into quantum computers
Xiao-Ming Zhang
Robust Quantum Reservoir Computing for Molecular Property Prediction
Daniel Beaulieu, Milan Kornjaca, Zoran Krunic, Michael Stivaktakis, Thomas Ehmer, Sheng-Tao Wang, Anh Pham
Robustly learning the Hamiltonian dynamics of a superconducting quantum processor.
Hangleiter D, Roth I, Fuksa J, Eisert J, Roushan P.
Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization
Nico Meyer, Julian Berberich, Christopher Mutschler, Daniel D. Scherer