Research of combined hybrid method applied in the Reissner-Mindlin plate model. - Zhu Wang 003; Bing Hu (Appl. Math. Comput., 2006)

Extrapolation Algorithms for Solving Mixed Boundary Integral Equations of the Helmholtz Equation by Mechanical Quadrature Methods. - Jin Huang 011; Zhu Wang 003 (SIAM J. Sci. Comput., 2009)

Two-level discretizations of nonlinear closure models for proper orthogonal decomposition. - Zhu Wang 003; Imran Akhtar; Jeff Borggaard; Traian Iliescu (J. Comput. Phys., 2011)

Artificial viscosity proper orthogonal decomposition. - Jeff Borggaard; Traian Iliescu; Zhu Wang 003 (Math. Comput. Model., 2011)

Non-iterative domain decomposition methods for a non-stationary Stokes-Darcy model with Beavers-Joseph interface condition. - Wenqiang Feng; Xiaoming He; Zhu Wang 003; Xu Zhang 003 (Appl. Math. Comput., 2012)

Asymptotic error expansions for hypersingular integrals. - Jin Huang 011; Zhu Wang 003; Rui Zhu (Adv. Comput. Math., 2013)

Variational multiscale proper orthogonal decomposition: Convection-dominated convection-diffusion-reaction equations. - Traian Iliescu; Zhu Wang 003 (Math. Comput., 2013)

Are the Snapshot Difference Quotients Needed in the Proper Orthogonal Decomposition? - Traian Iliescu; Zhu Wang 003 (SIAM J. Sci. Comput., 2014)

A goal-oriented reduced-order modeling approach for nonlinear systems. - Jeff Borggaard; Zhu Wang 003; Lizette Zietsman (Comput. Math. Appl., 2016)

Approximate partitioned method of snapshots for POD. - Zhu Wang 003; Brian McBee; Traian Iliescu (J. Comput. Appl. Math., 2016)

A Variational Approach to the Inverse Photolithography Problem. - Luca Rondi; Fadil Santosa; Zhu Wang 003 (SIAM J. Appl. Math., 2016)

Adjoint-Based, Superconvergent Galerkin Approximations of Linear Functionals. - Bernardo Cockburn; Zhu Wang 003 (J. Sci. Comput., 2017)

Preface of 2nd Annual Meeting of SIAM Central States Section. - Xiaoming He; Stephen Pankavich; Erik S. Van Vleck; Zhu Wang 003; Xiu Ye (Comput. Math. Appl., 2018)

Efficient time domain decomposition algorithms for parabolic PDE-constrained optimization problems. - Jun Liu 025; Zhu Wang 003 (Comput. Math. Appl., 2018)

Numerical analysis of the Leray reduced order model. - Xuping Xie; David R. Wells; Zhu Wang 003; Traian Iliescu (J. Comput. Appl. Math., 2018)

POD/DEIM Reduced-Order Modeling of Time-Fractional Partial Differential Equations with Applications in Parameter Identification. - Hongfei Fu 002; Hong Wang 018; Zhu Wang 003 (J. Sci. Comput., 2018)

An Ensemble Algorithm for Numerical Solutions to Deterministic and Random Parabolic PDEs. - Yan Luo; Zhu Wang 003 (SIAM J. Numer. Anal., 2018)

A Second-Order Time-Stepping Scheme for Simulating Ensembles of Parameterized Flow Problems. - Max D. Gunzburger; Nan Jiang 003; Zhu Wang 003 (Comput. Methods Appl. Math., 2019)

Non-commutative discretize-then-optimize algorithms for elliptic PDE-constrained optimal control problems. - Jun Liu 025; Zhu Wang 003 (J. Comput. Appl. Math., 2019)

Conservative explicit local time-stepping schemes for the shallow water equations. - Thi-Thao-Phuong Hoang; Wei Leng; Lili Ju; Zhu Wang 003; Konstantin Pieper (J. Comput. Phys., 2019)

A Multilevel Monte Carlo Ensemble Scheme for Random Parabolic PDEs. - Yan Luo; Zhu Wang 003 (SIAM J. Sci. Comput., 2019)

Reduced Order Models for the Quasi-Geostrophic Equations: A Brief Survey. - Changhong Mou; Zhu Wang 003; David R. Wells; Xuping Xie; Traian Iliescu (CoRR, 2020)

A ROM-accelerated parallel-in-time preconditioner for solving all-at-once systems from evolutionary PDEs. - Jun Liu 025; Zhu Wang 003 (CoRR, 2020)

POD-(H)DG Method for Incompressible Flow Simulations. - Guosheng Fu; Zhu Wang 003 (J. Sci. Comput., 2020)

Nonoverlapping Localized Exponential Time Differencing Methods for Diffusion Problems. - Thi-Thao-Phuong Hoang; Lili Ju; Zhu Wang 003 (J. Sci. Comput., 2020)

High order explicit local time stepping methods for hyperbolic conservation laws. - Thi-Thao-Phuong Hoang; Lili Ju; Wei Leng; Zhu Wang 003 (Math. Comput., 2020)

Structure-Preserving Galerkin POD-DEIM Reduced-Order Modeling of Hamiltonian Systems. - Zhu Wang 003 (CoRR, 2021)

Nonlinear Level Set Learning for Function Approximation on Sparse Data with Applications to Parametric Differential Equations. - Anthony D. Gruber; Max D. Gunzburger; Lili Ju; Yuankai Teng; Zhu Wang 003 (CoRR, 2021)

Learning Green's Functions of Linear Reaction-Diffusion Equations with Application to Fast Numerical Solver. - Yuankai Teng; Xiaoping Zhang 005; Zhu Wang 003; Lili Ju (CoRR, 2021)

An efficient iterative method for solving parameter-dependent and random diffusion problems. - Xiaobing Feng 001; Yan Luo; Liet Vo; Zhu Wang 003 (CoRR, 2021)

Parallel Exponential Time Differencing Methods for Geophysical Flow Simulations. - Rihui Lan; Wei Leng; Zhu Wang 003; Lili Ju; Max D. Gunzburger (CoRR, 2021)

Bilinear Control of Convection-Cooling: From Open-Loop to Closed-Loop. - Weiwei Hu; Jun Liu 025; Zhu Wang 003 (CoRR, 2021)

Hamiltonian Operator Inference: Physics-preserving Learning of Reduced-order Models for Hamiltonian Systems. - Harsh Sharma; Zhu Wang 003; Boris Kramer (CoRR, 2021)

A Comparison of Neural Network Architectures for Data-Driven Reduced-Order Modeling. - Anthony D. Gruber; Max D. Gunzburger; Lili Ju; Zhu Wang 003 (CoRR, 2021)

Nonlinear Reduced DNN Models for State Estimation. - Wolfgang Dahmen; Min Wang; Zhu Wang 003 (CoRR, 2021)

Level set learning with pseudo-reversible neural networks for nonlinear dimension reduction in function approximation. - Yuankai Teng; Zhu Wang 003; Lili Ju; Anthony D. Gruber; Guannan Zhang (CoRR, 2021)

A FOM/ROM Hybrid Approach for Accelerating Numerical Simulations. - Lihong Feng; Guosheng Fu; Zhu Wang 003 (J. Sci. Comput., 2021)

Learning Green’s Functions of Linear Reaction-Diffusion Equations with Application to Fast Numerical Solver. - Yuankai Teng; Xiaoping Zhang 005; Zhu Wang 003; Lili Ju (MSML, 2022)

A ROM-accelerated parallel-in-time preconditioner for solving all-at-once systems in unsteady convection-diffusion PDEs. - Jun Liu 025; Zhu Wang 003 (Appl. Math. Comput., 2022)

Energetically Consistent Model Reduction for Metriplectic Systems. - Anthony D. Gruber; Max D. Gunzburger; Lili Ju; Zhu Wang 003 (CoRR, 2022)

A hyper-reduced MAC scheme for the parametric Stokes and Navier-Stokes equations. - Yanlai Chen; Lijie Ji; Zhu Wang 003 (J. Comput. Phys., 2022)

High-order multirate explicit time-stepping schemes for the baroclinic-barotropic split dynamics in primitive equations. - Rihui Lan; Lili Ju; Zhu Wang 003; Max D. Gunzburger; Philip Jones (J. Comput. Phys., 2022)

An Efficient Iterative Method for Solving Parameter-Dependent and Random Convection-Diffusion Problems. - Xiaobing Feng 001; Yan Luo; Liet Vo; Zhu Wang 003 (J. Sci. Comput., 2022)

Verifiability of the Data-Driven Variational Multiscale Reduced Order Model. - Birgul Koc; Changhong Mou; Honghu Liu; Zhu Wang 003; Gianluigi Rozza; Traian Iliescu (J. Sci. Comput., 2022)

A Multifidelity Monte Carlo Method for Realistic Computational Budgets. - Anthony D. Gruber; Max D. Gunzburger; Lili Ju; Zhu Wang 003 (J. Sci. Comput., 2023)

Level Set Learning with Pseudoreversible Neural Networks for Nonlinear Dimension Reduction in Function Approximation. - Yuankai Teng; Zhu Wang 003; Lili Ju; Anthony D. Gruber; Guannan Zhang (SIAM J. Sci. Comput., 2023)

Gradient Preserving Operator Inference: Data-Driven Reduced-Order Models for Equations with Gradient Structure. - Yuwei Geng; Jasdeep Singh; Lili Ju; Boris Kramer; Zhu Wang 003 (CoRR, 2024)

A deep learning method for the dynamics of classic and conservative Allen-Cahn equations based on fully-discrete operators. - Yuwei Geng; Yuankai Teng; Zhu Wang 003; Lili Ju (J. Comput. Phys., 2024)

Data-Driven Reduced-Order Models for Port-Hamiltonian Systems with Operator Inference. - Yuwei Geng; Lili Ju; Boris Kramer; Zhu Wang 003 (CoRR, 2025)

Expansive Natural Neural Gradient Flows for Energy Minimization. - Wolfgang Dahmen; Wuchen Li; Yuankai Teng; Zhu Wang 003 (CoRR, 2025)