Loading [MathJax]/jax/output/HTML-CSS/config.js
Close Search Advanced
Journals
Resources
About Us
Open Access
Journals
Resources
About Us
Open Access

All Journals

Zhi-Qin John Xu

Results

A Correction and Comments on “Multi-Scale Deep Neural Network (MscaleDNN) for Solving Poisson-Boltzmann Equation in Complex Domains CiCP, 28 (5): 1970–2001, 2020”

Journal Article

A Correction and Comments on “Multi-Scale Deep Neural Network (MscaleDNN) for Solving Poisson-Boltzmann Equation in Complex Domains CiCP, 28 (5): 1970–2001, 2020”

Communications in Computational Physics, Vol. 33 (2023), Iss. 5 : pp. 1509–1513

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

Journal Article

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

Communications in Computational Physics, Vol. 32 (2022), Iss. 2 : pp. 299–335

Info
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks

Journal Article

Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks

Communications in Computational Physics, Vol. 28 (2020), Iss. 5 : pp. 1746–1767

Info
A Multi-Scale DNN Algorithm for Nonlinear Elliptic Equations with Multiple Scales

Journal Article

A Multi-Scale DNN Algorithm for Nonlinear Elliptic Equations with Multiple Scales

Communications in Computational Physics, Vol. 28 (2020), Iss. 5 : pp. 1886–1906

Info
Multi-Scale Deep Neural Network (MscaleDNN) for Solving Poisson-Boltzmann Equation in Complex Domains

Journal Article

Multi-Scale Deep Neural Network (MscaleDNN) for Solving Poisson-Boltzmann Equation in Complex Domains

Communications in Computational Physics, Vol. 28 (2020), Iss. 5 : pp. 1970–2001

Info
Implicit Bias in Understanding Deep Learning for Solving PDEs Beyond Ritz-Galerkin Method

Journal Article

Implicit Bias in Understanding Deep Learning for Solving PDEs Beyond Ritz-Galerkin Method

CSIAM Transactions on Applied Mathematics, Vol. 3 (2022), Iss. 2 : pp. 299–317

Info
Theory of the Frequency Principle for General Deep Neural Networks

Journal Article

Theory of the Frequency Principle for General Deep Neural Networks

CSIAM Transactions on Applied Mathematics, Vol. 2 (2021), Iss. 3 : pp. 484–507

Info
Embedding Principle: A Hierarchical Structure of Loss Landscape of Deep Neural Networks

Journal Article

Embedding Principle: A Hierarchical Structure of Loss Landscape of Deep Neural Networks

Journal of Machine Learning, Vol. 1 (2022), Iss. 1 : pp. 60–113

Read Now
Embedding Principle in Depth for the Loss Landscape Analysis of Deep Neural Networks

Journal Article

Embedding Principle in Depth for the Loss Landscape Analysis of Deep Neural Networks

CSIAM Transactions on Applied Mathematics, Vol. 5 (2024), Iss. 2 : pp. 350–389

Info
Phase Diagram of Initial Condensation for Two-Layer Neural Networks

Journal Article

Phase Diagram of Initial Condensation for Two-Layer Neural Networks

CSIAM Transactions on Applied Mathematics, Vol. 5 (2024), Iss. 3 : pp. 448–514

Info
Loss Jump During Loss Switch in Solving PDEs with Neural Networks

Journal Article

Loss Jump During Loss Switch in Solving PDEs with Neural Networks

Communications in Computational Physics, Vol. 36 (2024), Iss. 4 : pp. 1090–1112

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

Journal Article

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

East Asian Journal on Applied Mathematics, Vol. 14 (2024), Iss. 4 : pp. 657–674

Info