16 citations · 61 across the 7 of their papers we have counts for
7 papers
Concentration of Data Encoding in Parameterized Quantum Circuits
Guangxi Li, Ruilin Ye, Xuanqiang Zhao +1
Variational quantum algorithms have been acknowledged as a leading strategy to realize near-term quantum advantages in meaningful tasks, including machine learning and combinatoria…
Quantum Self-Attention Neural Networks for Text Classification
Guangxi Li, Xuanqiang Zhao, Xin Wang
An emerging direction of quantum computing is to establish meaningful quantum applications in various fields of artificial intelligence, including natural language processing (NLP)…
A Hybrid Quantum-Classical Hamiltonian Learning Algorithm
Youle Wang, Guangxi Li, Xin Wang
Hamiltonian learning is crucial to the certification of quantum devices and quantum simulators. In this paper, we propose a hybrid quantum-classical Hamiltonian learning algorithm…
VSQL: Variational Shadow Quantum Learning for Classification
Guangxi Li, Zhixin Song, Xin Wang
Classification of quantum data is essential for quantum machine learning and near-term quantum technologies. In this paper, we propose a new hybrid quantum-classical framework for…
Block-term Tensor Neural Networks
Jinmian Ye, Guangxi Li, Di Chen +3
Deep neural networks (DNNs) have achieved outstanding performance in a wide range of applications, e.g., image classification, natural language processing, etc. Despite the good pe…
Variational quantum Gibbs state preparation with a truncated Taylor series
Youle Wang, Guangxi Li, Xin Wang
The preparation of quantum Gibbs state is an essential part of quantum computation and has wide-ranging applications in various areas, including quantum simulation, quantum optimiz…
Quantum Data Fitting Algorithm for Non-sparse Matrices
Guangxi Li, Youle Wang, Yu Luo +1
We propose a quantum data fitting algorithm for non-sparse matrices, which is based on the Quantum Singular Value Estimation (QSVE) subroutine and a novel efficient method for reco…