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 2557-2568 of 4,297
Quixer: A Quantum Transformer Model
Nikhil Khatri, Gabriel Matos, Luuk Coopmans, Stephen Clark
Qureka! Box -- An ENSAR methodology based tool for understanding quantum computing concepts
Abhishek Purohit, Jose Jorge Christen, Richard Kienhoefer, Simon Armstrong, Maninder Kaur, Araceli Venegas-Gomez
QWalkVec: Node Embedding by Quantum Walk
Rei Sato, Shuichiro Haruta, Kazuhiro Saito, Mori Kurokawa
Realizing Quantum Kernel Models at Scale with Matrix Product State Simulation
Mekena Metcalf, Pablo Andrés-Martínez, Nathan Fitzpatrick
Red-QAOA: Efficient Variational Optimization through Circuit Reduction
Meng Wang, Bo Fang, Ang Li, Prashant Nair
Redefining Lexicographical Ordering: Optimizing Pauli String Decompositions for Quantum Compiling
Qunsheng Huang, David Winderl, Arianne Meijer-van de Griend, Richie Yeung
Reexamination of the realtime protection for user privacy in practical quantum private query
Chun-Yan Wei, Xiao-Qiu Cai, Tian-Yin Wang
Regression of Concurrence via Local Unitary Invariants.
Li M, Wang W, Zhang X, Wang J, Li L, Shen S.
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