Quantum Machine Learning
3,957 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 601-612 of 3,957
Learning Hamiltonians in the Heisenberg limit with static single-qubit fields
Shrigyan Brahmachari, Shuchen Zhu, Iman Marvian, Yu Tong
Learning high-dimensional quantum entanglement through physics-guided neural networks
Yang Xu, Hao Zhang, Wenwen Zhang, Luchang Niu, Girish Kulkarni, Mahtab Amooei, Sergio Carbajo, Robert W. Boyd
Learning Non-Markovian Noise via Ensemble Optimal Control
Da-Wei Luo, Ting Yu
Learning parameter curves in feedback-based quantum optimization algorithms
Vicente Peña Pérez, Matthew D. Grace, Christian Arenz, Alicia B. Magann
Learning partial transpose signatures in qubit ququart states from a few measurements
Christian Candeago, Paolo Da Rold, Michele Grossi, Pawel Horodecki, Antonio Mandarino
Learning Relationship between Quantum Walks and Underdamped Langevin Dynamics
Yazhen Wang
Learning spectral density functions in open quantum systems
Felipe Peleteiro, João Victor Shiguetsugo Kawanami Lima, Pedro Marcelo Prado, Felipe Fernandes Fanchini, Ariel Norambuena
Learning Temporal Patterns in Financial Time Series: A Comparative Study of Quantum LSTM and Quantum Reservoir Computing
Danyal Maheshwari, Gerhard Hellstern, Martin Zaefferer, Martin Braun, Tanja Döhler
Learning to Build Quantum Kernels: A Reinforcement Learning Framework for Quantum SVC Optimization
Barbato L, Buonaiuto G, Marassi L, Marrone S, Sansone C, Esposito M, Gargiulo F.
Learning Volterra Kernels for Non-Markovian Open Quantum Systems
Jimmie Adriazola, Katarzyna Roszak
Leveraging Time Series Foundation Models to Detect Performance Anomalies in Software Systems
Federico Di Menna, Luca Traini, Vittorio Cortellessa
Lie-Algebraic Analysis of Generators: Approximation-Error Bounds and Barren-Plateau Heuristics
Hiroshi Ohno