Quantum Machine Learning
521 papers for year 2024
Showing 421-432 of 521
Regressions on quantum neural networks at maximal expressivity.
Panadero I, Ban Y, Espinós H, Puebla R, Casanova J, Torrontegui E.
Reinforcement learning with learned gadgets to tackle hard quantum problems on real hardware
Akash Kundu, Leopoldo Sarra
Reinforcement learning-based architecture search for quantum machine learning
Frederic Rapp, David A. Kreplin, Marco F. Huber, Marco Roth
Representing arbitrary ground states of toric code by a restricted Boltzmann machine
Penghua Chen, Bowen Yan, Shawn X. Cui
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