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 2113-2124 of 3,957
Qonductor: A Cloud Orchestrator for Quantum Computing
Emmanouil Giortamis, Francisco Romão, Nathaniel Tornow, Dmitry Lugovoy, Pramod Bhatotia
QOPS: A Compiler Framework for Quantum Circuit Simulation Acceleration with Profile Guided Optimizations
Yu-Tsung Wu, Po-Hsuan Huang, Kai-Chieh Chang, Chia-Heng Tu, Shih-Hao Hung
QSRA: A QPU Scheduling and Resource Allocation Approach for Cloud-Based Quantum Computing
Binhan Lu, Zhaoyun Chen, Yuchun Wu
QTRL: Toward Practical Quantum Reinforcement Learning via Quantum-Train
Chen-Yu Liu, Chu-Hsuan Abraham Lin, Chao-Han Huck Yang, Kuan-Cheng Chen, Min-Hsiu Hsieh
Quadratic Advantage with Quantum Randomized Smoothing Applied to Time-Series Analysis
Nicola Franco, Marie Kempkes, Jakob Spiegelberg, Jeanette Miriam Lorenz
QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation
Zhuo Chen, Rumen Dangovski, Charlotte Loh, Owen Dugan, Di Luo, Marin Soljačić
Quantifying entanglement for unknown quantum states via artificial neural networks.
Pan GZ, Yang M, Zhou J, Yuan H, Miao C, Zhang G.
Quantum Active Learning
Yongcheng Ding, Yue Ban, Mikel Sanz, José D. Martín-Guerrero, Xi Chen
Quantum Advantage with Faulty Oracle
David Rasmussen Lolck, Laura Mančinska, Manaswi Paraashar
Quantum Algorithm for a Stochastic Multicloud Model
Kazumasa Ueno, Hiroaki Miura
Quantum Algorithm for Online Exp-concave Optimization
Jianhao He, Chengchang Liu, Xutong Liu, Lvzhou Li, John C. S. Lui
Quantum Algorithm for Sparse Online Learning with Truncated Gradient Descent
Debbie Lim, Yixian Qiu, Patrick Rebentrost, Qisheng Wang