Zhu Wang

Orcid: 0000-0002-7821-8574

Affiliations:
  • University of South Carolina, Department of Mathematics, Columbia, SC, USA


According to our database1, Zhu Wang authored at least 48 papers between 2006 and 2024.

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Bibliography

2024
A deep learning method for the dynamics of classic and conservative Allen-Cahn equations based on fully-discrete operators.
J. Comput. Phys., January, 2024

Gradient Preserving Operator Inference: Data-Driven Reduced-Order Models for Equations with Gradient Structure.
CoRR, 2024

2023
Level Set Learning with Pseudoreversible Neural Networks for Nonlinear Dimension Reduction in Function Approximation.
SIAM J. Sci. Comput., June, 2023

A Multifidelity Monte Carlo Method for Realistic Computational Budgets.
J. Sci. Comput., 2023

2022
Verifiability of the Data-Driven Variational Multiscale Reduced Order Model.
J. Sci. Comput., 2022

An Efficient Iterative Method for Solving Parameter-Dependent and Random Convection-Diffusion Problems.
J. Sci. Comput., 2022

High-order multirate explicit time-stepping schemes for the baroclinic-barotropic split dynamics in primitive equations.
J. Comput. Phys., 2022

A hyper-reduced MAC scheme for the parametric Stokes and Navier-Stokes equations.
J. Comput. Phys., 2022

Energetically Consistent Model Reduction for Metriplectic Systems.
CoRR, 2022

A ROM-accelerated parallel-in-time preconditioner for solving all-at-once systems in unsteady convection-diffusion PDEs.
Appl. Math. Comput., 2022

Learning Green’s Functions of Linear Reaction-Diffusion Equations with Application to Fast Numerical Solver.
Proceedings of the Mathematical and Scientific Machine Learning, 2022

2021
A FOM/ROM Hybrid Approach for Accelerating Numerical Simulations.
J. Sci. Comput., 2021

Level set learning with pseudo-reversible neural networks for nonlinear dimension reduction in function approximation.
CoRR, 2021

Nonlinear Reduced DNN Models for State Estimation.
CoRR, 2021

A Comparison of Neural Network Architectures for Data-Driven Reduced-Order Modeling.
CoRR, 2021

Hamiltonian Operator Inference: Physics-preserving Learning of Reduced-order Models for Hamiltonian Systems.
CoRR, 2021

Bilinear Control of Convection-Cooling: From Open-Loop to Closed-Loop.
CoRR, 2021

Parallel Exponential Time Differencing Methods for Geophysical Flow Simulations.
CoRR, 2021

An efficient iterative method for solving parameter-dependent and random diffusion problems.
CoRR, 2021

Learning Green's Functions of Linear Reaction-Diffusion Equations with Application to Fast Numerical Solver.
CoRR, 2021

Nonlinear Level Set Learning for Function Approximation on Sparse Data with Applications to Parametric Differential Equations.
CoRR, 2021

Structure-Preserving Galerkin POD-DEIM Reduced-Order Modeling of Hamiltonian Systems.
CoRR, 2021

2020
High order explicit local time stepping methods for hyperbolic conservation laws.
Math. Comput., 2020

Nonoverlapping Localized Exponential Time Differencing Methods for Diffusion Problems.
J. Sci. Comput., 2020

POD-(H)DG Method for Incompressible Flow Simulations.
J. Sci. Comput., 2020

A ROM-accelerated parallel-in-time preconditioner for solving all-at-once systems from evolutionary PDEs.
CoRR, 2020

Reduced Order Models for the Quasi-Geostrophic Equations: A Brief Survey.
CoRR, 2020

2019
A Multilevel Monte Carlo Ensemble Scheme for Random Parabolic PDEs.
SIAM J. Sci. Comput., 2019

Conservative explicit local time-stepping schemes for the shallow water equations.
J. Comput. Phys., 2019

Non-commutative discretize-then-optimize algorithms for elliptic PDE-constrained optimal control problems.
J. Comput. Appl. Math., 2019

A Second-Order Time-Stepping Scheme for Simulating Ensembles of Parameterized Flow Problems.
Comput. Methods Appl. Math., 2019

2018
An Ensemble Algorithm for Numerical Solutions to Deterministic and Random Parabolic PDEs.
SIAM J. Numer. Anal., 2018

POD/DEIM Reduced-Order Modeling of Time-Fractional Partial Differential Equations with Applications in Parameter Identification.
J. Sci. Comput., 2018

Numerical analysis of the Leray reduced order model.
J. Comput. Appl. Math., 2018

Efficient time domain decomposition algorithms for parabolic PDE-constrained optimization problems.
Comput. Math. Appl., 2018

Preface of 2nd Annual Meeting of SIAM Central States Section.
Comput. Math. Appl., 2018

2017
Adjoint-Based, Superconvergent Galerkin Approximations of Linear Functionals.
J. Sci. Comput., 2017

2016
A Variational Approach to the Inverse Photolithography Problem.
SIAM J. Appl. Math., 2016

Approximate partitioned method of snapshots for POD.
J. Comput. Appl. Math., 2016

A goal-oriented reduced-order modeling approach for nonlinear systems.
Comput. Math. Appl., 2016

2014
Are the Snapshot Difference Quotients Needed in the Proper Orthogonal Decomposition?
SIAM J. Sci. Comput., 2014

2013
Variational multiscale proper orthogonal decomposition: Convection-dominated convection-diffusion-reaction equations.
Math. Comput., 2013

Asymptotic error expansions for hypersingular integrals.
Adv. Comput. Math., 2013

2012
Non-iterative domain decomposition methods for a non-stationary Stokes-Darcy model with Beavers-Joseph interface condition.
Appl. Math. Comput., 2012

2011
Artificial viscosity proper orthogonal decomposition.
Math. Comput. Model., 2011

Two-level discretizations of nonlinear closure models for proper orthogonal decomposition.
J. Comput. Phys., 2011

2009
Extrapolation Algorithms for Solving Mixed Boundary Integral Equations of the Helmholtz Equation by Mechanical Quadrature Methods.
SIAM J. Sci. Comput., 2009

2006
Research of combined hybrid method applied in the Reissner-Mindlin plate model.
Appl. Math. Comput., 2006


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