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Zhiping Mao
Zhiping Mao
School of Mathematical Sciences Xiamen University
Verified email at xmu.edu.cn
Title
Cited by
Cited by
Year
DeepXDE: A deep learning library for solving differential equations
L Lu, X Meng, Z Mao, GE Karniadakis
SIAM review 63 (1), 208-228, 2021
14042021
Physics-informed neural networks for high-speed flows
Z Mao, AD Jagtap, GE Karniadakis
Computer Methods in Applied Mechanics and Engineering 360, 112789, 2020
7672020
Physics-informed neural networks (PINNs) for fluid mechanics: A review
S Cai, Z Mao, Z Wang, M Yin, GE Karniadakis
Acta Mechanica Sinica 37 (12), 1727-1738, 2021
7272021
What is the fractional Laplacian?
A Lischke, G Pang, M Gulian, F Song, C Glusa, X Zheng, Z Mao, W Cai, ...
arXiv preprint arXiv:1801.09767, 2018
412*2018
A comprehensive and fair comparison of two neural operators (with practical extensions) based on fair data
L Lu, X Meng, S Cai, Z Mao, S Goswami, Z Zhang, GE Karniadakis
Computer Methods in Applied Mechanics and Engineering 393, 114778, 2022
2712022
Analysis and approximation of a fractional Cahn--Hilliard equation
M Ainsworth, Z Mao
SIAM Journal on Numerical Analysis 55 (4), 1689-1718, 2017
1572017
Physics-informed neural networks for inverse problems in supersonic flows
AD Jagtap, Z Mao, N Adams, GE Karniadakis
Journal of Computational Physics 466, 111402, 2022
1392022
DeepM&Mnet for hypersonics: Predicting the coupled flow and finite-rate chemistry behind a normal shock using neural-network approximation of operators
Z Mao, L Lu, O Marxen, TA Zaki, GE Karniadakis
Journal of computational physics 447, 110698, 2021
1152021
Efficient and accurate spectral method using generalized Jacobi functions for solving Riesz fractional differential equations
Z Mao, S Chen, J Shen
Applied Numerical Mathematics 106, 165-181, 2016
982016
Efficient spectral–Galerkin methods for fractional partial differential equations with variable coefficients
Z Mao, J Shen
Journal of Computational Physics 307, 243-261, 2016
972016
A spectral method (of exponential convergence) for singular solutions of the diffusion equation with general two-sided fractional derivative
Z Mao, GE Karniadakis
SIAM Journal on Numerical Analysis 56 (1), 24-49, 2018
902018
A generalized spectral collocation method with tunable accuracy for fractional differential equations with end-point singularities
F Zeng, Z Mao, GE Karniadakis
SIAM Journal on Scientific Computing 39 (1), A360-A383, 2017
752017
Hermite spectral methods for fractional PDEs in unbounded domains
Z Mao, J Shen
SIAM Journal on Scientific Computing 39 (5), A1928-A1950, 2017
662017
Well-posedness of the Cahn–Hilliard equation with fractional free energy and its Fourier Galerkin approximation
M Ainsworth, Z Mao
Chaos, Solitons & Fractals 102, 264-273, 2017
522017
Spectral element method with geometric mesh for two-sided fractional differential equations
Z Mao, J Shen
Advances in Computational Mathematics 44, 745-771, 2018
412018
Learning functional priors and posteriors from data and physics
X Meng, L Yang, Z Mao, J del Įguila Ferrandis, GE Karniadakis
Journal of Computational Physics 457, 111073, 2022
382022
Multi-domain spectral collocation method for variable-order nonlinear fractional differential equations
T Zhao, Z Mao, GE Karniadakis
Computer Methods in Applied Mechanics and Engineering 348, 377-395, 2019
292019
Nonlocal flocking dynamics: learning the fractional order of PDEs from particle simulations
Z Mao, Z Li, GE Karniadakis
Communications on Applied Mathematics and Computation 1, 597-619, 2019
252019
Fractional Burgers equation with nonlinear non-locality: Spectral vanishing viscosity and local discontinuous Galerkin methods
Z Mao, GE Karniadakis
Journal of Computational Physics 336, 143-163, 2017
232017
A fast solver for spectral elements applied to fractional differential equations using hierarchical matrix approximation
X Li, Z Mao, N Wang, F Song, H Wang, GE Karniadakis
Computer Methods in Applied Mechanics and Engineering 366, 113053, 2020
112020
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