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 757-768 of 4,297
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 thermodynamic master equations for open quantum systems
Peter Sentz, Stanley Nicholson, Yujin Cho, Sohail Reddy, Brendan Keith, Stefanie Günther
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 to Reconstruct Wigner Functions in Phase Space
Xinyu Tang, Yi-hsin Lin, Yan Zhu, Tailong Xiao, Yuxuan Du, Giulio Chiribella, Qiongyi He, Ya-dong Wu
Learning Volterra Kernels for Non-Markovian Open Quantum Systems
Jimmie Adriazola, Katarzyna Roszak
Leveraging machine learning for the synthesis optimization of tea waste–derived carbon quantum dots for supercapacitor electrodes
Ayisha Naziba Thaha, Karthikeyan Subburamu, Subramanian Paravaikkarasu Pillai, Djanaguiraman Maduraimuthu, Jeya Sundara Sharmila Devasahayam, Ramesh Desikan
Leveraging Metrologically Useful States in Quantum Reservoir Networks
Erik L. Connerty, Margarite LaBorde, Ethan N. Evans
Leveraging Pretrained Neural Network Models for the Classification of Tumor Cells Analyzed by Label-Free Phase Holotomographic Microscopy.
Losa LVC, Douglas TA, Santos L, Monteiro R, Calejo I, Canadas RF, Nieder JB