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Kailiang Wu
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2020 – today
- 2024
- [j38]Chaoyi Cai, Jianxian Qiu, Kailiang Wu:
Provably convergent Newton-Raphson methods for recovering primitive variables with applications to physical-constraint-preserving Hermite WENO schemes for relativistic hydrodynamics. J. Comput. Phys. 498: 112669 (2024) - [j37]Shengrong Ding, Kailiang Wu:
GQL-based bound-preserving and locally divergence-free central discontinuous Galerkin schemes for relativistic magnetohydrodynamics. J. Comput. Phys. 514: 113208 (2024) - [j36]Linfeng Xu, Shengrong Ding, Kailiang Wu
:
High-Order Accurate Entropy Stable Schemes for Relativistic Hydrodynamics with General Synge-Type Equation of State. J. Sci. Comput. 98(2): 43 (2024) - [j35]Wei Chen, Kailiang Wu, Tao Xiong:
High Order Structure-Preserving Finite Difference WENO Schemes for MHD Equations with Gravitation in all Sonic Mach Numbers. J. Sci. Comput. 99(2): 36 (2024) - [j34]Shumo Cui, Shengrong Ding, Kailiang Wu
:
On Optimal Cell Average Decomposition for High-Order Bound-Preserving Schemes of Hyperbolic Conservation Laws. SIAM J. Numer. Anal. 62(2): 775-810 (2024) - [j33]Shengrong Ding, Kailiang Wu
:
A New Discretely Divergence-Free Positivity-Preserving High-Order Finite Volume Method for Ideal MHD Equations. SIAM J. Sci. Comput. 46(1): 50- (2024) - [j32]Alina Chertock, Alexander Kurganov
, Michael Redle, Kailiang Wu
:
A New Locally Divergence-Free Path-Conservative Central-Upwind Scheme for Ideal and Shallow Water Magnetohydrodynamics. SIAM J. Sci. Comput. 46(3): 1998- (2024) - [j31]Ce Zhang
, Kailiang Wu
, Zhihai He
:
Critical Sampling for Robust Evolution Operator Learning of Unknown Dynamical Systems. IEEE Trans. Artif. Intell. 5(6): 2856-2871 (2024) - [c1]Junfeng Chen, Kailiang Wu:
Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning. ICML 2024 - [i32]Shengrong Ding, Kailiang Wu:
GQL-Based Bound-Preserving and Locally Divergence-Free Central Discontinuous Galerkin Schemes for Relativistic Magnetohydrodynamics. CoRR abs/2402.15437 (2024) - [i31]Jiangfu Wang, Huazhong Tang, Kailiang Wu:
High-order accurate positivity-preserving and well-balanced discontinuous Galerkin schemes for ten-moment Gaussian closure equations with source terms. CoRR abs/2402.15446 (2024) - [i30]Shumo Cui, Alexander Kurganov, Kailiang Wu:
Bound-Preserving Framework for Central-Upwind Schemes for General Hyperbolic Conservation Laws. CoRR abs/2403.13420 (2024) - [i29]Chaoyi Cai, Jianxian Qiu, Kailiang Wu:
Provably Convergent and Robust Newton-Raphson Method: A New Dawn in Primitive Variable Recovery for Relativistic MHD. CoRR abs/2404.05531 (2024) - [i28]Mengqing Liu, Kailiang Wu:
Structure-Preserving Oscillation-Eliminating Discontinuous Galerkin Schemes for Ideal MHD Equations: Locally Divergence-Free and Positivity-Preserving. CoRR abs/2404.16794 (2024) - [i27]Junfeng Chen, Kailiang Wu:
Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning. CoRR abs/2405.09285 (2024) - 2023
- [j30]Shumo Cui, Shengrong Ding, Kailiang Wu:
Is the classic convex decomposition optimal for bound-preserving schemes in multiple dimensions? J. Comput. Phys. 476: 111882 (2023) - [j29]Wei Chen, Kailiang Wu, Tao Xiong:
High order asymptotic preserving finite difference WENO schemes with constrained transport for MHD equations in all sonic Mach numbers. J. Comput. Phys. 488: 112240 (2023) - [j28]Yupeng Ren, Kailiang Wu, Jianxian Qiu, Yulong Xing
:
On high order positivity-preserving well-balanced finite volume methods for the Euler equations with gravitation. J. Comput. Phys. 492: 112429 (2023) - [j27]Junfeng Chen, Kailiang Wu:
Deep-OSG: Deep learning of operators in semigroup. J. Comput. Phys. 493: 112498 (2023) - [j26]Kailiang Wu, Haili Jiang, Chi-Wang Shu
:
Provably Positive Central Discontinuous Galerkin Schemes via Geometric Quasilinearization for Ideal MHD Equations. SIAM J. Numer. Anal. 61(1): 250-285 (2023) - [j25]Kailiang Wu
, Chi-Wang Shu
:
Geometric Quasilinearization Framework for Analysis and Design of Bound-Preserving Schemes. SIAM Rev. 65(4): 1031-1073 (2023) - [i26]Junfeng Chen, Kailiang Wu:
Deep-OSG: A deep learning approach for approximating a family of operators in semigroup to model unknown autonomous systems. CoRR abs/2302.03358 (2023) - [i25]Ce Zhang, Kailiang Wu, Zhihai He:
Critical Sampling for Robust Evolution Operator Learning of Unknown Dynamical Systems. CoRR abs/2304.07485 (2023) - [i24]Chaoyi Cai, Jianxian Qiu, Kailiang Wu:
Provably convergent Newton-Raphson methods for recovering primitive variables with applications to physical-constraint-preserving Hermite WENO schemes for relativistic hydrodynamics. CoRR abs/2305.14805 (2023) - [i23]Shengrong Ding, Kailiang Wu:
A new discretely divergence-free positivity-preserving high-order finite volume method for ideal MHD equations. CoRR abs/2305.14820 (2023) - [i22]Manting Peng, Zheng Sun, Kailiang Wu:
OEDG: Oscillation-eliminating discontinuous Galerkin method for hyperbolic conservation laws. CoRR abs/2310.04807 (2023) - 2022
- [j24]Zhen Chen, Victor Churchill, Kailiang Wu, Dongbin Xiu:
Deep neural network modeling of unknown partial differential equations in nodal space. J. Comput. Phys. 449: 110782 (2022) - [j23]Haili Jiang, Huazhong Tang, Kailiang Wu:
Positivity-preserving well-balanced central discontinuous Galerkin schemes for the Euler equations under gravitational fields. J. Comput. Phys. 463: 111297 (2022) - [j22]Yaping Chen, Kailiang Wu:
A physical-constraint-preserving finite volume WENO method for special relativistic hydrodynamics on unstructured meshes. J. Comput. Phys. 466: 111398 (2022) - [j21]Zheng Sun
, Yuanzhe Wei
, Kailiang Wu
:
On Energy Laws and Stability of Runge-Kutta Methods for Linear Seminegative Problems. SIAM J. Numer. Anal. 60(5): 2448-2481 (2022) - [i21]Zheng Sun, Yuanzhe Wei, Kailiang Wu:
On Energy Laws and Stability of Runge-Kutta Methods for Linear Seminegative Problems. CoRR abs/2201.06501 (2022) - [i20]Kailiang Wu, Haili Jiang, Chi-Wang Shu:
Provably Positive Central DG Schemes via Geometric Quasilinearization for Ideal MHD Equations. CoRR abs/2203.14853 (2022) - [i19]Shumo Cui, Shengrong Ding, Kailiang Wu:
Is the Classic Convex Decomposition Optimal for Bound-Preserving Schemes in Multiple Dimensions? CoRR abs/2207.08849 (2022) - [i18]Yaping Chen, Kailiang Wu:
A Physical-Constraint-Preserving Finite Volume WENO Method for Special Relativistic Hydrodynamics on Unstructured Meshes. CoRR abs/2207.09385 (2022) - [i17]Haili Jiang, Huazhong Tang, Kailiang Wu:
Positivity-Preserving Well-Balanced Central Discontinuous Galerkin Schemes for the Euler Equations under Gravitational Fields. CoRR abs/2207.09398 (2022) - [i16]Wei Chen, Kailiang Wu, Tao Xiong:
High order asymptotic preserving finite difference WENO schemes with constrained transport for MHD equations in all sonic Mach numbers. CoRR abs/2211.16655 (2022) - [i15]Alina Chertock, Alexander Kurganov, Michael Redle, Kailiang Wu:
A New Locally Divergence-Free Path-Conservative Central-Upwind Scheme for Ideal and Shallow Water Magnetohydrodynamics. CoRR abs/2212.02682 (2022) - [i14]Shumo Cui, Shengrong Ding, Kailiang Wu:
On Optimal Cell Average Decomposition for High-Order Bound-Preserving Schemes of Hyperbolic Conservation Laws. CoRR abs/2212.05045 (2022) - 2021
- [j20]Kailiang Wu, Chi-Wang Shu
:
Provably physical-constraint-preserving discontinuous Galerkin methods for multidimensional relativistic MHD equations. Numerische Mathematik 148(3): 699-741 (2021) - [j19]Kailiang Wu
, Yulong Xing:
Uniformly High-Order Structure-Preserving Discontinuous Galerkin Methods for Euler Equations with Gravitation: Positivity and Well-Balancedness. SIAM J. Sci. Comput. 43(1): A472-A510 (2021) - [j18]Kailiang Wu
:
Minimum Principle on Specific Entropy and High-Order Accurate Invariant-Region-Preserving Numerical Methods for Relativistic Hydrodynamics. SIAM J. Sci. Comput. 43(6): B1164-B1197 (2021) - [i13]Kailiang Wu:
Minimum Principle on Specific Entropy and High-Order Accurate Invariant Region Preserving Numerical Methods for Relativistic Hydrodynamics. CoRR abs/2102.03801 (2021) - [i12]Zhen Chen, Victor Churchill, Kailiang Wu, Dongbin Xiu:
Deep Neural Network Modeling of Unknown Partial Differential Equations in Nodal Space. CoRR abs/2106.03603 (2021) - [i11]Kailiang Wu, Chi-Wang Shu:
Geometric Quasilinearization Framework for Analysis and Design of Bound-Preserving Schemes. CoRR abs/2111.04722 (2021) - 2020
- [j17]Kailiang Wu
, Dongbin Xiu:
Data-driven deep learning of partial differential equations in modal space. J. Comput. Phys. 408: 109307 (2020) - [j16]Zhen Chen, Kailiang Wu
, Dongbin Xiu:
Methods to Recover Unknown Processes in Partial Differential Equations Using Data. J. Sci. Comput. 85(2): 23 (2020) - [j15]Kailiang Wu
, Chi-Wang Shu
:
Entropy Symmetrization and High-Order Accurate Entropy Stable Numerical Schemes for Relativistic MHD Equations. SIAM J. Sci. Comput. 42(4): A2230-A2261 (2020) - [j14]Kailiang Wu
, Tong Qin
, Dongbin Xiu:
Structure-Preserving Method for Reconstructing Unknown Hamiltonian Systems From Trajectory Data. SIAM J. Sci. Comput. 42(6): A3704-A3729 (2020) - [i10]Kailiang Wu, Chi-Wang Shu:
Provably Physical-Constraint-Preserving Discontinuous Galerkin Methods for Multidimensional Relativistic MHD Equations. CoRR abs/2002.03371 (2020) - [i9]Jun Hou, Tong Qin
, Kailiang Wu, Dongbin Xiu:
A Non-Intrusive Correction Algorithm for Classification Problems with Corrupted Data. CoRR abs/2002.04658 (2020) - [i8]Zhen Chen, Kailiang Wu, Dongbin Xiu:
Methods to Recover Unknown Processes in Partial Differential Equations Using Data. CoRR abs/2003.02387 (2020) - [i7]Kailiang Wu, Yulong Xing:
Uniformly High-Order Structure-Preserving Discontinuous Galerkin Methods for Euler Equations with Gravitation: Positivity and Well-Balancedness. CoRR abs/2005.07166 (2020)
2010 – 2019
- 2019
- [j13]Kailiang Wu
, Dongbin Xiu:
Numerical aspects for approximating governing equations using data. J. Comput. Phys. 384: 200-221 (2019) - [j12]Tong Qin
, Kailiang Wu
, Dongbin Xiu:
Data driven governing equations approximation using deep neural networks. J. Comput. Phys. 395: 620-635 (2019) - [j11]Kailiang Wu
, Chi-Wang Shu
:
Provably positive high-order schemes for ideal magnetohydrodynamics: analysis on general meshes. Numerische Mathematik 142(4): 995-1047 (2019) - [i6]Kailiang Wu, Tong Qin
, Dongbin Xiu:
Structure-preserving Method for Reconstructing Unknown Hamiltonian Systems from Trajectory Data. CoRR abs/1905.10396 (2019) - [i5]Kailiang Wu, Chi-Wang Shu:
Entropy Symmetrization and High-Order Accurate Entropy Stable Numerical Schemes for Relativistic MHD Equations. CoRR abs/1907.07467 (2019) - [i4]Kailiang Wu, Dongbin Xiu:
Data-Driven Deep Learning of Partial Differential Equations in Modal Space. CoRR abs/1910.06948 (2019) - 2018
- [j10]Kailiang Wu
, Dongbin Xiu:
Sequential function approximation on arbitrarily distributed point sets. J. Comput. Phys. 354: 370-386 (2018) - [j9]Yeonjong Shin
, Kailiang Wu
, Dongbin Xiu:
Sequential function approximation with noisy data. J. Comput. Phys. 371: 363-381 (2018) - [j8]Kailiang Wu
:
Positivity-Preserving Analysis of Numerical Schemes for Ideal Magnetohydrodynamics. SIAM J. Numer. Anal. 56(4): 2124-2147 (2018) - [j7]Kailiang Wu
, Chi-Wang Shu
:
A Provably Positive Discontinuous Galerkin Method for Multidimensional Ideal Magnetohydrodynamics. SIAM J. Sci. Comput. 40(5): B1302-B1329 (2018) - [i3]Kailiang Wu
, Dongbin Xiu:
An Explicit Neural Network Construction for Piecewise Constant Function Approximation. CoRR abs/1808.07390 (2018) - [i2]Kailiang Wu, Dongbin Xiu:
Numerical Aspects for Approximating Governing Equations Using Data. CoRR abs/1809.09170 (2018) - [i1]Tong Qin, Kailiang Wu, Dongbin Xiu:
Data Driven Governing Equations Approximation Using Deep Neural Networks. CoRR abs/1811.05537 (2018) - 2017
- [j6]Kailiang Wu
, Huazhong Tang, Dongbin Xiu:
A stochastic Galerkin method for first-order quasilinear hyperbolic systems with uncertainty. J. Comput. Phys. 345: 224-244 (2017) - [j5]Kailiang Wu
, Yeonjong Shin
, Dongbin Xiu:
A Randomized Tensor Quadrature Method for High Dimensional Polynomial Approximation. SIAM J. Sci. Comput. 39(5) (2017) - 2016
- [j4]Kailiang Wu
, Huazhong Tang:
A Direct Eulerian GRP Scheme for Spherically Symmetric General Relativistic Hydrodynamics. SIAM J. Sci. Comput. 38(3) (2016) - 2015
- [j3]Kailiang Wu
, Huazhong Tang:
High-order accurate physical-constraints-preserving finite difference WENO schemes for special relativistic hydrodynamics. J. Comput. Phys. 298: 539-564 (2015) - 2014
- [j2]Kailiang Wu
, Huazhong Tang:
Finite volume local evolution Galerkin method for two-dimensional relativistic hydrodynamics. J. Comput. Phys. 256: 277-307 (2014) - [j1]Kailiang Wu
, Zhicheng Yang, Huazhong Tang:
A third-order accurate direct Eulerian GRP scheme for the Euler equations in gas dynamics. J. Comput. Phys. 264: 177-208 (2014)
Coauthor Index
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last updated on 2024-09-04 00:27 CEST by the dblp team
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