Quantum Machine Learning
248 papers for year 2022
Showing 157-168 of 248
QDataSet, quantum datasets for machine learning.
Perrier E, Youssry A, Ferrie C.
QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning
Di Luo, Jiayu Shen, Rumen Dangovski, Marin Soljačić
QuanGCN: Noise-Adaptive Training for Robust Quantum Graph Convolutional Networks
Kaixiong Zhou, Zhenyu Zhang, Shengyuan Chen, Tianlong Chen, Xiao Huang, Zhangyang Wang, Xia Hu
Quantifying $T$-gate-count improvements for ground-state-energy estimation with near-optimal state preparation
Shivesh Pathak, Antonio Russo, Stefan Seritan, Andrew Baczewski
Quantum Algorithm for Anomaly Detection of Sequences
Ming-Chao Guo, Hai-Ling Liu, Shi-Jie Pan, Wen-Min Li, Su-Juan Qin, Xin-Yi Huang, Fei Gao, Qiao-Yan Wen
Quantum Algorithms for Identifying Hidden Strings with Applications to Matroid Problems
Xiaowei Huang, Shihao Zhang, Lvzhou Li
Quantum algorithms for quantum dynamics
Alexander Miessen, Pauline J. Ollitrault, Francesco Tacchino, Ivano Tavernelli
Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants
Andrew M. Childs, Tongyang Li, Jin-Peng Liu, Chunhao Wang, Ruizhe Zhang
Quantum Clustering with k-Means: a Hybrid Approach
Alessandro Poggiali, Alessandro Berti, Anna Bernasconi, Gianna M. Del Corso, Riccardo Guidotti
Quantum Computing Methods for Supply Chain Management
Hansheng Jiang, Zuo-Jun Max Shen, Junyu Liu
Quantum deep recurrent reinforcement learning
Samuel Yen-Chi Chen
Quantum divide and conquer
Andrew M. Childs, Robin Kothari, Matt Kovacs-Deak, Aarthi Sundaram, Daochen Wang