26 citations · 34 across the 8 of their papers we have counts for
9 papers
An Efficient Explicit Implementation of a Quantum Algorithm with Quantum Advantage for Nonlinear Scalar Conservation Laws
Kezhen Wang, Junpeng Hu, Lei Zhang
Quantum algorithms for nonlinear partial differential equations remain challenging because nonlinear dynamics are not directly amenable to unitary quantum simulation. Building on t…
Quantum Random Feature Method for Solving Partial Differential Equations
Junpeng Hu, Shi Jin, Nana Liu +1
Quantum computing holds significant promise for scientific computing due to its potential for polynomial to even exponential speedups over classical methods, which are often hinder…
A quantum gradient descent algorithm for optimizing Gaussian Process models
Junpeng Hu, Jinglai Li, Lei Zhang +1
Gaussian Process Regression (GPR) is a nonparametric supervised learning method, widely valued for its ability to quantify uncertainty. Despite its advantages and broad application…
Quantum Circuits for partial differential equations via Schrödingerisation
Junpeng Hu, Shi Jin, Nana Liu +1
Quantum computing has emerged as a promising avenue for achieving significant speedup, particularly in large-scale PDE simulations, compared to classical computing. One of the main…
Dilation theorem via Schrödingerisation, with applications to the quantum simulation of differential equations
Junpeng Hu, Shi Jin, Nana Liu +1
Nagy's unitary dilation theorem in operator theory asserts the possibility of dilating a contraction into a unitary operator. When used in quantum computing, its practical implemen…
Quantum Algorithms for Multiscale Partial Differential Equations
Junpeng Hu, Shi Jin, Lei Zhang
Partial differential equation (PDE) models with multiple temporal/spatial scales are prevalent in several disciplines such as physics, engineering, and many others. These models ar…
On multilevel Monte Carlo methods for deterministic and uncertain hyperbolic systems
Junpeng Hu, Shi Jin, Jinglai Li +1
In this paper, we evaluate the performance of the multilevel Monte Carlo method (MLMC) for deterministic and uncertain hyperbolic systems, where randomness is introduced either in…
Spatio-Temporal Neural Network for Fitting and Forecasting COVID-19
Yi-Shuai Niu, Wentao Ding, Junpeng Hu +2
We established a Spatio-Temporal Neural Network, namely STNN, to forecast the spread of the coronavirus COVID-19 outbreak worldwide in 2020. The basic structure of STNN is similar…
A Difference-of-Convex Programming Approach With Parallel Branch-and-Bound For Sentence Compression Via A Hybrid Extractive Model
Yi-Shuai Niu, Yu You, Wenxu Xu +3
Sentence compression is an important problem in natural language processing with wide applications in text summarization, search engine and human-AI interaction system etc. In this…