Zhi-Qin John Xu

Publication Activity (10 Years)

Years Active: 2018-2025
Publications (10 Years): 64

Top Topics

Inverse Problems

Matrix Completion

Top Venues

Publications

Xiong-bin Yan, Zhi-Qin John Xu, Zheng Ma
Bayesian Inversion with Neural Operator (BINO) for modeling subdiffusion: Forward and inverse problems. J. Comput. Appl. Math. 454 (2025)
Tianyi Chen, Zhi-Qin John Xu
Efficient and Flexible Method for Reducing Moderate-size Deep Neural Networks with Condensation. CoRR (2024)
Zhongwang Zhang, Pengxiao Lin, Zhiwei Wang, Yaoyu Zhang, Zhi-Qin John Xu
Initialization is Critical to Whether Transformers Fit Composite Functions by Inference or Memorizing. CoRR (2024)
Zhangchen Zhou, Yaoyu Zhang, Zhi-Qin John Xu
A rationale from frequency perspective for grokking in training neural network. CoRR (2024)
Tianyi Chen, Zhi-Qin John Xu
Efficient and Flexible Method for Reducing Moderate-Size Deep Neural Networks with Condensation. Entropy 26 (7) (2024)
Zhiwei Wang, Lulu Zhang, Zhongwang Zhang, Zhi-Qin John Xu
Loss Jump During Loss Switch in Solving PDEs with Neural Networks. CoRR (2024)
Zhongwang Zhang, Zhi-Qin John Xu
Implicit Regularization of Dropout. IEEE Trans. Pattern Anal. Mach. Intell. 46 (6) (2024)
Zhongwang Zhang, Yuqing Li, Tao Luo, Zhi-Qin John Xu
Stochastic Modified Equations and Dynamics of Dropout Algorithm. ICLR (2024)
Hanxu Zhou, Yuan Zhang, Guangjie Leng, Ruofan Wang, Zhi-Qin John Xu
Understanding Time Series Anomaly State Detection through One-Class Classification. CoRR (2024)
Zhongwang Zhang, Zhiwei Wang, Junjie Yao, Zhangchen Zhou, Xiaolong Li, Weinan E, Zhi-Qin John Xu
Anchor function: a type of benchmark functions for studying language models. CoRR (2024)
Zhi-Qin John Xu, Junjie Yao, Yuxiao Yi, Liangkai Hang, Weinan E, Yaoyu Zhang, Tianhan Zhang
Solving multiscale dynamical systems by deep learning. CoRR (2024)
Zhiwei Wang, Yunji Wang, Zhongwang Zhang, Zhangchen Zhou, Hui Jin, Tianyang Hu, Jiacheng Sun, Zhenguo Li, Yaoyu Zhang, Zhi-Qin John Xu
Towards Understanding How Transformer Perform Multi-step Reasoning with Matching Operation. CoRR (2024)
Zhongwang Zhang, Zhi-Qin John Xu
Loss Spike in Training Neural Networks. CoRR (2023)
Xi-An Li, Jinran Wu, Zhi-Qin John Xu, You-Gan Wang
Solving a class of multi-scale elliptic PDEs by means of Fourier-based mixed physics informed neural networks. CoRR (2023)
Zhongwang Zhang, Yuqing Li, Tao Luo, Zhi-Qin John Xu
Stochastic Modified Equations and Dynamics of Dropout Algorithm. CoRR (2023)
Runze Mao, Minqi Lin, Yan Zhang, Tianhan Zhang, Zhi-Qin John Xu, Zhi X. Chen
: A deep learning empowered open-source platform for reacting flow simulations. Comput. Phys. Commun. 291 (2023)
Zhangchen Zhou, Hanxu Zhou, Yuqing Li, Zhi-Qin John Xu
Understanding the Initial Condensation of Convolutional Neural Networks. CoRR (2023)
Xiong-bin Yan, Keke Wu, Zhi-Qin John Xu, Zheng Ma
An Unsupervised Deep Learning Approach for the Wave Equation Inverse Problem. CoRR (2023)
Zhengan Chen, Yuqing Li, Tao Luo, Zhangchen Zhou, Zhi-Qin John Xu
Phase Diagram of Initial Condensation for Two-layer Neural Networks. CoRR (2023)
Xi-An Li, Zhi-Qin John Xu, Lei Zhang
Subspace decomposition based DNN algorithm for elliptic type multi-scale PDEs. J. Comput. Phys. 488 (2023)
Xiong-bin Yan, Zhi-Qin John Xu, Zheng Ma
Laplace-fPINNs: Laplace-based fractional physics-informed neural networks for solving forward and inverse problems of subdiffusion. CoRR (2023)
Leyang Zhang, Zhi-Qin John Xu, Tao Luo, Yaoyu Zhang
Limitation of Characterizing Implicit Regularization by Data-independent Functions. Trans. Mach. Learn. Res. 2023 (2023)
Yaoyu Zhang, Zhongwang Zhang, Leyang Zhang, Zhiwei Bai, Tao Luo, Zhi-Qin John Xu
Optimistic Estimate Uncovers the Potential of Nonlinear Models. CoRR (2023)
Yaoyu Zhang, Zhongwang Zhang, Leyang Zhang, Zhiwei Bai, Tao Luo, Zhi-Qin John Xu
Linear Stability Hypothesis and Rank Stratification for Nonlinear Models. CoRR (2022)
Xiong-bin Yan, Zhi-Qin John Xu, Zheng Ma
Bayesian Inversion with Neural Operator (BINO) for Modeling Subdiffusion: Forward and Inverse Problems. CoRR (2022)
Zhiwei Wang, Yaoyu Zhang, Yiguang Ju, Weinan E, Zhi-Qin John Xu, Tianhan Zhang
A deep learning-based model reduction (DeePMR) method for simplifying chemical kinetics. CoRR (2022)
Tianhan Zhang, Yuxiao Yi, Yifan Xu, Zhi X. Chen, Yaoyu Zhang, Weinan E, Zhi-Qin John Xu
A multi-scale sampling method for accurate and robust deep neural network to predict combustion chemical kinetics. CoRR (2022)
Hanxu Zhou, Qixuan Zhou, Zhenyuan Jin, Tao Luo, Yaoyu Zhang, Zhi-Qin John Xu
Empirical Phase Diagram for Three-layer Neural Networks with Infinite Width. CoRR (2022)
Shuyu Yin, Tao Luo, Peilin Liu, Zhi-Qin John Xu
An Experimental Comparison Between Temporal Difference and Residual Gradient with Neural Network Approximation. CoRR (2022)
Leyang Zhang, Zhi-Qin John Xu, Tao Luo, Yaoyu Zhang
Limitation of characterizing implicit regularization by data-independent functions. CoRR (2022)
Tao Luo, Zheng Ma, Zhi-Qin John Xu, Yaoyu Zhang
On the Exact Computation of Linear Frequency Principle Dynamics and Its Generalization. SIAM J. Math. Data Sci. 4 (4) (2022)
Zhongwang Zhang, Zhi-Qin John Xu
Implicit regularization of dropout. CoRR (2022)
Zhi-Qin John Xu, Yaoyu Zhang, Tao Luo
Overview frequency principle/spectral bias in deep learning. CoRR (2022)
Zhiwei Bai, Tao Luo, Zhi-Qin John Xu, Yaoyu Zhang
Embedding Principle in Depth for the Loss Landscape Analysis of Deep Neural Networks. CoRR (2022)
Zhemin Li, Zhi-Qin John Xu, Tao Luo, Hongxia Wang
A regularised deep matrix factorised model of matrix completion for image restoration. IET Image Process. 16 (12) (2022)
Yaoyu Zhang, Yuqing Li, Zhongwang Zhang, Tao Luo, Zhi-Qin John Xu
Embedding Principle: a hierarchical structure of loss landscape of deep neural networks. CoRR (2021)
Tao Luo, Zhi-Qin John Xu, Zheng Ma, Yaoyu Zhang
Phase Diagram for Two-layer ReLU Neural Networks at Infinite-width Limit. J. Mach. Learn. Res. 22 (2021)
Yaoyu Zhang, Zhongwang Zhang, Tao Luo, Zhi-Qin John Xu
Embedding Principle of Loss Landscape of Deep Neural Networks. CoRR (2021)
Lulu Zhang, Zhi-Qin John Xu, Yaoyu Zhang
Data-informed Deep Optimization. CoRR (2021)
Tao Luo, Zheng Ma, Zhiwei Wang, Zhi-Qin John Xu, Yaoyu Zhang
An Upper Limit of Decaying Rate with Respect to Frequency in Deep Neural Network. CoRR (2021)
Zhongwang Zhang, Hanxu Zhou, Zhi-Qin John Xu
A variance principle explains why dropout finds flatter minima. CoRR (2021)
Yuheng Ma, Zhi-Qin John Xu, Jiwei Zhang
Frequency Principle in Deep Learning Beyond Gradient-descent-based Training. CoRR (2021)
Lulu Zhang, Tao Luo, Yaoyu Zhang, Zhi-Qin John Xu, Zheng Ma
MOD-Net: A Machine Learning Approach via Model-Operator-Data Network for Solving PDEs. CoRR (2021)
Zhi-Qin John Xu, Hanxu Zhou, Tao Luo, Yaoyu Zhang
Towards Understanding the Condensation of Two-layer Neural Networks at Initial Training. CoRR (2021)
Guangjie Leng, Yekun Zhu, Zhi-Qin John Xu
Force-in-domain GAN inversion. CoRR (2021)
Xi-An Li, Zhi-Qin John Xu, Lei Zhang
Subspace Decomposition based DNN algorithm for elliptic type multi-scale PDEs. CoRR (2021)
Yaoyu Zhang, Tao Luo, Zheng Ma, Zhi-Qin John Xu
Linear Frequency Principle Model to Understand the Absence of Overfitting in Neural Networks. CoRR (2021)
Tao Luo, Zheng Ma, Zhiwei Wang, Zhi-Qin John Xu, Yaoyu Zhang
Fourier-domain Variational Formulation and Its Well-posedness for Supervised Learning. CoRR (2020)
Tao Luo, Zhi-Qin John Xu, Zheng Ma, Yaoyu Zhang
Phase diagram for two-layer ReLU neural networks at infinite-width limit. CoRR (2020)
Zhemin Li, Zhi-Qin John Xu, Tao Luo, Hongxia Wang
A regularized deep matrix factorized model of matrix completion for image restoration. CoRR (2020)
Zhi-Qin John Xu, Hanxu Zhou
Deep frequency principle towards understanding why deeper learning is faster. CoRR (2020)
Yaoyu Zhang, Zhi-Qin John Xu, Tao Luo, Zheng Ma
A type of generalization error induced by initialization in deep neural networks. MSML (2020)
Ziqi Liu, Wei Cai, Zhi-Qin John Xu
Multi-scale Deep Neural Network (MscaleDNN) for Solving Poisson-Boltzmann Equation in Complex Domains. CoRR (2020)
Tao Luo, Zheng Ma, Zhi-Qin John Xu, Yaoyu Zhang
On the exact computation of linear frequency principle dynamics and its generalization. CoRR (2020)
Jihong Wang, Zhi-Qin John Xu, Jiwei Zhang, Yaoyu Zhang
Implicit bias with Ritz-Galerkin method in understanding deep learning for solving PDEs. CoRR (2020)
Wei Cai, Zhi-Qin John Xu
Multi-scale Deep Neural Networks for Solving High Dimensional PDEs. CoRR (2019)
Yaoyu Zhang, Zhi-Qin John Xu, Tao Luo, Zheng Ma
A type of generalization error induced by initialization in deep neural networks. CoRR (2019)
Zhi-Qin John Xu, Yaoyu Zhang, Tao Luo, Yanyang Xiao, Zheng Ma
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks. CoRR (2019)
Yaoyu Zhang, Zhi-Qin John Xu, Tao Luo, Zheng Ma
Explicitizing an Implicit Bias of the Frequency Principle in Two-layer Neural Networks. CoRR (2019)
Zhi-Qin John Xu, Douglas Zhou, David Cai
Dynamical and Coupling Structure of Pulse-Coupled Networks in Maximum Entropy Analysis. Entropy 21 (1) (2019)
Tao Luo, Zheng Ma, Zhi-Qin John Xu, Yaoyu Zhang
Theory of the Frequency Principle for General Deep Neural Networks. CoRR (2019)
Zhi-Qin John Xu, Yaoyu Zhang, Yanyang Xiao
Training Behavior of Deep Neural Network in Frequency Domain. ICONIP (1) (2019)
Zhi-Qin John Xu
Frequency Principle in Deep Learning with General Loss Functions and Its Potential Application. CoRR (2018)
Zhi-Qin John Xu, Jennifer Crodelle, Douglas Zhou, David Cai
Maximum Entropy Principle Analysis in Network Systems with Short-time Recordings. CoRR (2018)