Quantum Machine Learning
4,009 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 1825-1836 of 4,009
Tight Generalization Bound for Supervised Quantum Machine Learning
Xin Wang, Rebing Wu
Time-series forecasting with multiphoton quantum states and integrated photonics
Rosario Di Bartolo, Simone Piacentini, Francesco Ceccarelli, Giacomo Corrielli, Roberto Osellame, Valeria Cimini, Fabio Sciarrino
TorchQuantumDistributed
Oliver Knitter, Jonathan Mei, Masako Yamada, Martin Roetteler
Toward Live Noise Fingerprinting in Quantum Software Engineering
Avner Bensoussan, Elena Chachkarova, Karine Even-Mendoza, Sophie Fortz, Vasileios Klimis
Toward Scalable Quantum Compilation for Modular Architecture: Qubit Mapping and Reuse via Deep Reinforcement Learning
Sang S, Hour L, Han Y.
Towards Continuous-variable Quantum Neural Networks for Biomedical Imaging
Daniel Alejandro Lopez, Oscar Montiel, Oscar Castillo, Miguel Lopez-Montiel
Towards Explainable Quantum AI: Informing the Encoder Selection of Quantum Neural Networks via Visualization
Shaolun Ruan, Feng Liang, Rohan Ramakrishna, Chao Ren, Rudai Yan, Qiang Guan, Jiannan Li, Yong Wang
Towards Personalized Quantum Federated Learning for Anomaly Detection
Ratun Rahman, Sina Shaham, Dinh C. Nguyen
Towards Quantum Enhanced Adversarial Robustness with Rydberg Reservoir Learning
Shehbaz Tariq, Muhammad Talha, Symeon Chatzinotas, Hyundong Shin
Towards Quantum Machine Learning of Lattice Boltzmann Collision Operators for Fluid Dynamic Simulations
Wael Itani, Katepalli R. Sreenivasan
Transdisciplinary approach to the concept of quantum technologies in management
Aleksandr N. Kuzminov, Sergey A. Nekrasov, Elena V. Polikarpova, Vitaly S. Polikarpov
Transferable Equivariant Quantum Circuits for TSP: Generalization Bounds and Empirical Validation
Monit Sharma, Hoong Chuin Lau