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 1921-1932 of 4,297
Offline Dedicated Quantum Attacks on Block Ciphers Constructions Based on Two Parallel Permutation-Based Pseudorandom Functions
Xiao-Fan Zhen, Zhen-Qiang Li, Jia-Cheng Fan, Su-Juan Qin, Fei Gao
On the Classical Shadow Nonparametric Bootstrap
Eric Ghysels, Jack Morgan
On the construction of graph models realizing given entropy vectors
Veronika E. Hubeny, Massimiliano Rota
On the Cryptographic Futility of Non-Collapsing Measurements
Alper Cakan, Dakshita Khurana, Tomoyuki Morimae, Yuki Shirakawa, Kabir Tomer, Takashi Yamakawa
One-Shot Structured Pruning of Quantum Neural Networks via $q$-Group Engineering and Quantum Geometric Metrics
Haijian Shao, Wei Liu, Xing Deng, Yingtao Jiang
OpenQudit: Extensible and Accelerated Numerical Quantum Compilation via a JIT-Compiled DSL
Ed Younis
Opportunities and Challenges for Data Quality in the Era of Quantum Computing
Sven Groppe, Valter Uotila, Jinghua Groppe
Optimal ancilla-free Clifford+T synthesis for general single-qubit unitaries
Hayata Morisaki, Kaoru Sano, Seiseki Akibue
Optimal quantum learning in proximity to universality
Moein N. Ivaki, Matias Karjula, Tapio Ala-Nissila
Optimal Scaling Quantum Interior Point Method for Linear Optimization
Mohammadhossein Mohammadisiahroudi, Zeguan Wu, Pouya Sampourmahani, Jun-Kai You, Tamás Terlaky
Optimising physical parameters of a quantum network based on a loss-jitter trade-off
Marcus J. Clark, Siddarth K. Joshi
Optimization of High-Fidelity Single-Qubit Gates for Fluxoniums Using Single-Flux Quantum Control
Maxime Lapointe-Major, Boyan Torosov, Bohdan Kulchytskyy, Pooya Ronagh