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 697-708 of 3,957
Neural network decoder confidence as a learned proxy for the logical gap
David Dentelski
Neural QAOA$^{2}$: Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization
Zubin Zheng, Jiahao Wu, Shengcai Liu
Neural Quantum States Based on Selected Configurations
Marco Julian Solanki, Lexin Ding, Markus Reiher
Neural Quantum States in Mixed Precision
Massimo Solinas, Agnes Valenti, Nawaf Bou-Rabee, Roeland Wiersema
Neural quantum support vector data description for one-class classification
Changjae Im, Hyeondo Oh, Daniel K. Park
Next-generation nano-biosensors for hepatocellular carcinoma.
Abuhassan Q, Saleh K, Roopashree R, Kanwar JB, Sudhakar T, Sharma V, Chauhan AS, Khaitova S
No Tile Left Behind: Multiprogramming for Surface-Code Architectures
Archisman Ghosh, Avimita Chatterjee, Swaroop Ghosh
Noise and Bandwidth Performance Optimization for Readout Electronics of DC Superconducting Quantum Interference Device
Yang Shao, Shandong Li, Fuqing Shang, Zhengyu Wang, Quanming Gao
Noise-aware selection of circuit cutting strategies under hardware noise non-uniformity
Debarthi Pal, Ritajit Majumdar, Padmanabha Venkatagiri Seshadri, Anupama Ray, Yogesh Simmhan
Noise-enhanced quantum kernels on analog quantum computers
Hsiang-Wei Huang, Shen-Liang Yang, Chuan-Chi Huang, Yueh-Nan Chen, Hong-Bin Chen
Noise-Resistant Feature-Aware Attack Detection Using Quantum Machine Learning
Chao Ding, Shi Wang, Jingtao Sun, Yaonan Wang, Daoyi Dong, Weibo Gao
Noisy Qubits, Hard Problems: A SystematicReview and Taxonomy of Quantum OptimizationBeyond Toy Benchmarks
Sridhara SK, Kumar KK.