Publications

Showing 33 of 33 publications
33
Robust Physics-Guided Diffusion for Full-Waveform Inversion

Jishen Peng, Enze Jiang, Zheng Ma, Xiongbin Yan

arXiv

2026journalpreprintFull-waveform InversionDiffusion models

PDF
32
DeepRTE: Pre-trained Attention-based Neural Network for Radiative Transfer

Yekun Zhu, Min Tang, Zheng Ma

Computer Methods in Applied Mechanics and Engineering

2026journalpublishedDeepRTEOperator Leraning

PDF
31
RT-APNN for Solving Gray Radiative Transfer Equations

Xizhe Xie, Wengu Chen, Zheng Ma, Han Wang

Communications in Computational Physics

2026journalto appearAPNNsRT-APNNGray-RTE

PDF
30
Asymptotic-Preserving Neural Networks based on Even-odd Decomposition for Multiscale Gray Radiative Transfer Equations

Keke Wu, Xizhe Xie, Wengu Chen, Han Wang, Zheng Ma

arXiv

2025journalpreprintAPNNsGray-RTE

PDF
29
Identification of the governing equation of stimulus-response data for run-and-tumble dynamics

Shicong Lei, Yu’an Li, Zheng Ma, Hepeng Zhang, Min Tang

PLOS Computational Biology

2025journalpublishedNeural NetworksChemotaxisPhotoresponse

PDF
28
A Deep Learning Approach for Solving the Inverse Problem of the Wave Equation

Xiong-Bin Yan, Keke Wu, Zhi-Qin John Xu, Zheng Ma

CSIAM Transactions on Applied Mathematics

2025journalpublishedFWIDeep LearningUnsupervised Learning

PDF
27
ODE-DPS: ODE-Based Diffusion Posterior Sampling for Linear Inverse Problems in Partial Differential Equation

Enze Jiang, Jishen Peng, Zheng Ma, Xiong-Bin Yan

Journal of Scientific Computing

2025journalpublishedInverse problemsODE-DPSDiffusion models

PDF
26
A micro-macro decomposition-based asymptotic-preserving random feature method for multiscale radiative transfer equations

Jingrun Chen, Zheng Ma, Keke Wu

Journal of Computational Physics

2025journalpublishedRadiative transferAPNNsRandom feature method

PDF
25
Bayesian Inversion with Neural Operator (BINO) for modeling subdiffusion: Forward and inverse problems

Xiong-Bin Yan, Zhi-Qin John Xu, Zheng Ma

Journal of Computational and Applied Mathematics

2025journalpublishedInverse problemsFractional DiffusionOperator LeraningBayesian

PDF
24
Capturing Shock Waves by Relaxation Neural Networks

Nan Zhou, Zheng Ma

arXiv

2024journalpreprintShocksConservation LawsPINNs

PDF
23
Laplace-fPINNs: Laplace-Based Fractional Physics-Informed Neural Networks for Solving Forward and Inverse Problems of a Time Fractional Equation

Xiong-Bin Yan, Zhi-Qin John Xu, Zheng Ma

East Asian Journal on Applied Mathematics

2024journalpublishedPINNsLaplace-fPINNsFractional

PDF
22
Asymptotic-Preserving Neural Networks for Multiscale Vlasov–Poisson–Fokker–Planck System in the High-Field Regime

Shi Jin, Zheng Ma, Tian-ai Zhang

Journal of Scientific Computing

2024journalpublishedAPNNsMultiscale Kinetic EquationsHigh-Field ScalingVlasov–Poisson–Fokker–Planck

PDF
21
Asymptotic-Preserving Neural Networks for Multiscale Kinetic Equations

Shi Jin, Zheng Ma, Keke Wu

Communications in Computational Physics

2024journalpublishedAPNNsMultiscale Kinetic Equations

PDF
20
Capturing the diffusive behavior of the multiscale linear transport equations by Asymptotic-Preserving Convolutional DeepONets

Keke Wu, Xiong-Bin Yan, Shi Jin, Zheng Ma

Computer Methods in Applied Mechanics and Engineering

2024journalpublishedAPNNsAPCONMultiscale Kinetic EquationsOperator Leraning

PDF
19
Asymptotic-Preserving Neural Networks for Multiscale Time-Dependent Linear Transport Equations

Shi Jin, Zheng Ma, Keke Wu

Journal of Scientific Computing

2023journalpublishedAPNNsLinear Transport EquationsUncertainty Quantification

PDF
18
Numerical Stability for Differential Equations with Memory

Guihong Wang, Yuqing Li, Tao Luo, Zheng Ma, Nung Kwan Yip, Guang Lin

arXiv

2023journalpreprintNumerical StabilityDifferential Equations with MemoryMulti-step Methods

PDF
17
On the Exact Computation of Linear Frequency Principle Dynamics and Its Generalization

Tao Luo, Zheng Ma, Zhi-Qin John Xu, Yaoyu Zhang

SIAM Journal on Mathematics of Data Science

2022journalpublishedDeep Leraning TheoryF-principle

PDF
16
Heat flux estimation of the cylinder in hypersonic rarefied flow based on neural network surrogate model

Dongming Ding, Hao Chen, Zheng Ma, Bin Zhang, Hong Liu

AIP Advances

2022journalpublishedDeep LearningSurrogate ModelingRarefied Flow

PDF
15
MOD-Net: A Machine Learning Approach via Model-Operator-Data Network for Solving PDEs

Lulu Zhang, Tao Luo, Yaoyu Zhang, Weinan E, Zhi-Qin John Xu, Zheng Ma

Communications in Computational Physics

2022journalpublishedOperator LeraningMOD-Net

PDF
14
An Upper Limit of Decaying Rate with Respect to Frequency in Deep Neural Network

Tao Luo, Zheng Ma, Zhiwei Wang, Zhi-Qin John Xu, Yaoyu Zhang

Proceedings of Mathematical and Scientific Machine Learning

2022conferencepublishedDeep Learning TheoryF-Principle

PDF
13
Phase Diagram for Two-layer ReLU Neural Networks at Infinite-width Limit

Tao Luo, Zhi-Qin John Xu, Zheng Ma, Yaoyu Zhang

Journal of Machine Learning Research

2021journalpublishedDeep Learning TheoryPhase Diagram

PDF
12
A Linear Frequency Principle Model to Understand the Absence of Overfitting in Neural Networks

Yaoyu Zhang, Tao Luo, Zheng Ma, Zhi-Qin John Xu

Chinese Physics Letters

2021journalpublishedDeep Learning TheoryFrequency Principle

PDF
11
Theory of the Frequency Principle for General Deep Neural Networks

Tao Luo, Zheng Ma, Zhi-Qin John Xu, Yaoyu Zhang

CSIAM Transactions on Applied Mathematics

2021journalpublishedDeep Learning TheoryF-principle

PDF
10
Trails in Kinetic Theory, Foundational Aspects and Numerical Methods

José Antonio Carrillo, Jingwei Hu, Zheng Ma, Thomas Rey

2021chapterpublishedKinetic TheoryGranular MaterialsSpectral Methods

PDF
9
A type of generalization error induced by initialization in deep neural networks

Yaoyu Zhang, Zhi-Qin John Xu, Tao Luo, Zheng Ma

Proceedings of Mathematical and Scientific Machine Learning

2020conferencepublishedDeep Learning TheoryASINTK

PDF
8
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks

Zhi-Qin John Xu, Yaoyu Zhang, Tao Luo, Yanyang Xiao, Zheng Ma

Communications in Computational Physics

2020journalpublishedDeep Learning TheoryFourier AnalysisFrequency Principle

PDF
7
Uniformly accurate machine learning-based hydrodynamic models for kinetic equations

Jiequn Han, Chao Ma, Zheng Ma, Weinan E

Proceedings of the National Academy of Sciences

2019journalpublishedBoltzmann EquationsModel ReductionHydrodynamic ApproximationGeneralized MomentsDeep Learning

PDF
6
Explicitizing an Implicit Bias of the Frequency Principle in Two-layer Neural Networks

Yaoyu Zhang, Zhi-Qin John Xu, Tao Luo, Zheng Ma

arXiv

2019journalpreprintDeep Learning TheoryImplicit Bias

PDF
5
A fast spectral method for the inelastic Boltzmann collision operator and application to heated granular gases

Jingwei Hu, Zheng Ma

Journal of Computational Physics

2019journalpublishedBoltzmann EquationsSpectral MethodsFast Algorithms

PDF
4
The Discrete Stochastic Galerkin Method for Hyperbolic Equations with Non-smooth and Random Coefficients

Shi Jin, Zheng Ma

Journal of Scientific Computing

2018journalpublishedHyperbolic EquationsUncertainty QuantificationgPC-SG

PDF
3
An improved semi-Lagrangian time splitting spectral method for the semi-classical Schrödinger equation with vector potentials using NUFFT

Zheng Ma, Yong Zhang, Zhennan Zhou

Applied Numerical Mathematics

2017journalpublishedSemi-classical SchrödingerTime Splitting Spectral MethodsNUFFT

PDF
2
Uniform spectral convergence of the stochastic Galerkin method for the linear transport equations with random inputs in diffusive regime and a micro–macro decomposition-based asymptotic-preserving method

Shi Jin, Jian-Guo Liu, Zheng Ma

Research in the Mathematical Sciences

2017journalpublishedgPC-SGAPUQNumerical Analysis

PDF
1
Explicit and Implicit TVD Schemes for Conservation Laws with Caputo Derivatives

Jian-Guo Liu, Zheng Ma, Zhennan Zhou

Journal of Scientific Computing

2017journalpublishedConservation LawsTVDFractional

PDF