Quantum generative adversarial network for generating discrete distribution
Quantum machine learning has recently attracted much attention from the community of
quantum computing. In this paper, we explore the ability of generative adversarial networks …
quantum computing. In this paper, we explore the ability of generative adversarial networks …
[HTML][HTML] A survey on HHL algorithm: From theory to application in quantum machine learning
Abstract The Harrow-Hassidim-Lloyd (HHL) algorithm is a method to solve the quantum
linear system of equations that may be found at the core of various scientific applications …
linear system of equations that may be found at the core of various scientific applications …
Quantum data compression by principal component analysis
Data compression can be achieved by reducing the dimensionality of high-dimensional but
approximately low-rank datasets, which may in fact be described by the variation of a much …
approximately low-rank datasets, which may in fact be described by the variation of a much …
Quantum machine learning for support vector machine classification
SS Kavitha, N Kaulgud - Evolutionary Intelligence, 2024 - Springer
Quantum machine learning aims to execute machine learning algorithms in quantum
computers by utilizing powerful laws like superposition and entanglement for solving …
computers by utilizing powerful laws like superposition and entanglement for solving …
Quantum algorithms for anomaly detection using amplitude estimation
M Guo, H Liu, Y Li, W Li, F Gao, S Qin, Q Wen - Physica A: Statistical …, 2022 - Elsevier
Anomaly detection, as an important branch of machine learning, plays a critical role in fraud
detection, health care, intrusion detection, military surveillance, etc. An anomaly detection …
detection, health care, intrusion detection, military surveillance, etc. An anomaly detection …
Toward implementing efficient image processing algorithms on quantum computers
F Yan, SE Venegas-Andraca, K Hirota - Soft Computing, 2023 - Springer
Quantum information science is an interdisciplinary subject spanning physics, mathematics,
and computer science. It involves finding new ways to apply natural quantum-mechanical …
and computer science. It involves finding new ways to apply natural quantum-mechanical …
Effective implementation of nonadiabatic geometric quantum gates of cat-state qubits using an auxiliary qutrit
YH Kang, Y Xiao, ZC Shi, Y Wang, JQ Yang… - New Journal of …, 2023 - iopscience.iop.org
We propose an effective protocol for the implementation of nonadiabatic geometric quantum
gates of cat-state qubits in Kerr-nonlinear resonators driven by two-photon squeezing drives …
gates of cat-state qubits in Kerr-nonlinear resonators driven by two-photon squeezing drives …
Quantum circuit learning with parameterized boson sampling
J Shi, Y Tang, Y Lu, Y Feng, R Shi… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A quantum circuit learning approach is studied to carry out the fast-fitting of Gaussian
functions. First, a parameterized structure is designed for quantum circuits based on the …
functions. First, a parameterized structure is designed for quantum circuits based on the …
Quantum algorithm for unsupervised anomaly detection
M Guo, S Pan, W Li, F Gao, S Qin, XL Yu… - Physica A: Statistical …, 2023 - Elsevier
Anomaly detection, an important branch of machine learning, plays a critical role in fraud
detection, health care, intrusion detection, military surveillance, etc. As one of the most …
detection, health care, intrusion detection, military surveillance, etc. As one of the most …
Improved quantum algorithm for A-optimal projection
SJ Pan, LC Wan, HL Liu, QL Wang, SJ Qin, QY Wen… - Physical Review A, 2020 - APS
Dimensionality reduction algorithms, which reduce the dimensionality of a given data set
whereas preserving the information of the original data set as well as possible, play an …
whereas preserving the information of the original data set as well as possible, play an …