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 1309-1320 of 4,009
Towards Practical Quantum Federated Learning: Enhancing Efficiency and Noise Tolerance
Suzukaze Kamei, Hideaki Kawaguchi, Takahiko Satoh
Towards Tensor Network Models for Low-Latency Jet Tagging on FPGAs
Alberto Coppi, Ema Puljak, Lorenzo Borella, Daniel Jaschke, Enrique Rico, Maurizio Pierini, Jacopo Pazzini, Andrea Triossi, Simone Montangero
Towards the implementation of a quantum classifier
Lorenzo Confalonieri
Towards Ultimate Accuracy in Quantum Multi-Class Classification: A Trace-Distance Binary Tree AdaBoost Classifier
Xin Wang, Yabo Wang, Rebing Wu
Toxicological Evaluation of Ionic Liquids: QSAR Approach for Acetylcholinesterase Enzyme Inhibition.
Ebrahimpoor Gorji A, Uusi-Kyyny P, Alopaeus V
Tracking the Catastrophic Collapse of Hybrid Exciton-Phonon Order in a Quantum Material
Hedayat H, Abdul-Aziz O, Comini D, Lang J, Bartel N, Buchhold M, Diehl S, Wolverson D, Sayers C, Cerullo G, Loosdrecht Pv.
TRADITIONAL CHINESE MUSICAL SYMBOLS IN GAME MUSIC: ONTOLOGY AND AESTHETIC ANALYSIS
BINGER HU, YEW YOONG CHONG
Trainability of IQP Quantum Circuit Born Machines Under Gaussian Initialization
Gennaro De Luca
Trainability-Oriented Hybrid Quantum Regression via Geometric Preconditioning and Curriculum Optimization
Qingyu Meng, Yangshuai Wang
Trainable Quantum Channels as Computational Primitives for Quantum Learning
Jingwei Wen, Ling Qian, Shijie Wei, Guilu Long
Training continuously-coupled reconfigurable photonic chips with quantum machine learning
Denis Stanev, Nicolò Spagnolo, Fabio Sciarrino
Training Students for Research with Quantum AI Simulation Tools
Tanay Kamlesh Patel, Niraj Anil Babar, Deep Pujara, Glen Uehara, Jean Larson, Andreas Spanias