Tao Luo - RankMe

50 papers A* 4B 1Journal 43Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Priori Estimates for Deep Residual Network in Continuous-Time Reinforcement Learning. SIAM J. Math. Data Sci. Shuyu Yin, Qixuan Zhou, Fei Wen, Tao Luo
2025	B	`conf`	Probing Implicit Bias in Semi-gradient Q-learning: Visualizing the Non-equilibrium Loss Landscapes via the Fokker-Planck Equation. IJCNN Shuyu Yin, Fei Wen, Peilin Liu, Tao Luo
2025	J	`jnl`	SSBE-PINN: A Sobolev Boundary Scheme Boosting Stability and Accuracy in Elliptic/Parabolic PDE Learning. CoRR Qixuan Zhou, Chuqi Chen, Tao Luo, Yang Xiang
2024	J	`jnl`	A priori Estimates for Deep Residual Network in Continuous-time Reinforcement Learning. CoRR Shuyu Yin, Qixuan Zhou, Fei Wen, Tao Luo
2024	J	`jnl`	Analyzing and Bridging the Gap between Maximizing Total Reward and Discounted Reward in Deep Reinforcement Learning. CoRR Shuyu Yin, Fei Wen, Peilin Liu, Tao Luo
2024	J	`jnl`	Demystifying Lazy Training of Neural Networks from a Macroscopic Viewpoint. CoRR Yuqing Li, Tao Luo, Qixuan Zhou
2024	J	`jnl`	Geometry of Critical Sets and Existence of Saddle Branches for Two-layer Neural Networks. CoRR Leyang Zhang, Yaoyu Zhang, Tao Luo
2024	J	`jnl`	Probing Implicit Bias in Semi-gradient Q-learning: Visualizing the Effective Loss Landscapes via the Fokker-Planck Equation. CoRR Shuyu Yin, Fei Wen, Peilin Liu, Tao Luo
2024	J	`jnl`	Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers. CoRR Chuqi Chen, Qixuan Zhou, Yahong Yang, Yang Xiang, Tao Luo
2024	A*	`conf`	Stochastic Modified Equations and Dynamics of Dropout Algorithm. ICLR Zhongwang Zhang, Yuqing Li, Tao Luo, Zhi-Qin John Xu
2023	J	`jnl`	Limitation of Characterizing Implicit Regularization by Data-independent Functions. Trans. Mach. Learn. Res. Leyang Zhang, Zhi-Qin John Xu, Tao Luo, Yaoyu Zhang
2023	J	`jnl`	On Residual Minimization for PDEs: Failure of PINN, Modified Equation, and Implicit Bias. CoRR Tao Luo, Qixuan Zhou
2023	J	`jnl`	Optimistic Estimate Uncovers the Potential of Nonlinear Models. CoRR Yaoyu Zhang, Zhongwang Zhang, Leyang Zhang, Zhiwei Bai, Tao Luo, Zhi-Qin John Xu
2023	J	`jnl`	Phase Diagram of Initial Condensation for Two-layer Neural Networks. CoRR Zhengan Chen, Yuqing Li, Tao Luo, Zhangchen Zhou, Zhi-Qin John Xu
2023	J	`jnl`	Stochastic Modified Equations and Dynamics of Dropout Algorithm. CoRR Zhongwang Zhang, Yuqing Li, Tao Luo, Zhi-Qin John Xu
2023	J	`jnl`	Structure and Gradient Dynamics Near Global Minima of Two-layer Neural Networks. CoRR Leyang Zhang, Yaoyu Zhang, Tao Luo
2022	J	`jnl`	A regularised deep matrix factorised model of matrix completion for image restoration. IET Image Process. Zhemin Li, Zhi-Qin John Xu, Tao Luo, Hongxia Wang
2022	J	`jnl`	An Experimental Comparison Between Temporal Difference and Residual Gradient with Neural Network Approximation. CoRR Shuyu Yin, Tao Luo, Peilin Liu, Zhi-Qin John Xu
2022	—	`conf`	An Upper Limit of Decaying Rate with Respect to Frequency in Linear Frequency Principle Model. MSML Tao Luo, Zheng Ma, Zhiwei Wang, Zhiqin John Xu, Yaoyu Zhang
2022	J	`jnl`	Embedding Principle in Depth for the Loss Landscape Analysis of Deep Neural Networks. CoRR Zhiwei Bai, Tao Luo, Zhi-Qin John Xu, Yaoyu Zhang
2022	A*	`conf`	Empirical Phase Diagram for Three-layer Neural Networks with Infinite Width. NeurIPS Hanxu Zhou, Qixuan Zhou, Zhenyuan Jin, Tao Luo, Yaoyu Zhang, Zhi-Qin John Xu
2022	J	`jnl`	Empirical Phase Diagram for Three-layer Neural Networks with Infinite Width. CoRR Hanxu Zhou, Qixuan Zhou, Zhenyuan Jin, Tao Luo, Yaoyu Zhang, Zhi-Qin John Xu
2022	J	`jnl`	Limitation of characterizing implicit regularization by data-independent functions. CoRR Leyang Zhang, Zhi-Qin John Xu, Tao Luo, Yaoyu Zhang
2022	J	`jnl`	Linear Stability Hypothesis and Rank Stratification for Nonlinear Models. CoRR Yaoyu Zhang, Zhongwang Zhang, Leyang Zhang, Zhiwei Bai, Tao Luo, Zhi-Qin John Xu
2022	J	`jnl`	Nonlinear Weighted Directed Acyclic Graph and A Priori Estimates for Neural Networks. SIAM J. Math. Data Sci. Yuqing Li, Tao Luo, Chao Ma
2022	J	`jnl`	On the Exact Computation of Linear Frequency Principle Dynamics and Its Generalization. SIAM J. Math. Data Sci. Tao Luo, Zheng Ma, Zhi-Qin John Xu, Yaoyu Zhang
2022	J	`jnl`	Overview frequency principle/spectral bias in deep learning. CoRR Zhi-Qin John Xu, Yaoyu Zhang, Tao Luo
2022	A*	`conf`	Towards Understanding the Condensation of Neural Networks at Initial Training. NeurIPS Hanxu Zhou, Qixuan Zhou, Tao Luo, Yaoyu Zhang, Zhi-Qin John Xu
2021	J	`jnl`	An Upper Limit of Decaying Rate with Respect to Frequency in Deep Neural Network. CoRR Tao Luo, Zheng Ma, Zhiwei Wang, Zhi-Qin John Xu, Yaoyu Zhang
2021	A*	`conf`	Embedding Principle of Loss Landscape of Deep Neural Networks. NeurIPS Yaoyu Zhang, Zhongwang Zhang, Tao Luo, Zhi-Qin John Xu
2021	J	`jnl`	Embedding Principle of Loss Landscape of Deep Neural Networks. CoRR Yaoyu Zhang, Zhongwang Zhang, Tao Luo, Zhi-Qin John Xu
2021	J	`jnl`	Embedding Principle: a hierarchical structure of loss landscape of deep neural networks. CoRR Yaoyu Zhang, Yuqing Li, Zhongwang Zhang, Tao Luo, Zhi-Qin John Xu
2021	J	`jnl`	Energy Scaling and Asymptotic Properties of One-Dimensional Discrete System with Generalized Lennard-Jones (m, n) Interaction. J. Nonlinear Sci. Tao Luo, Yang Xiang, Nung Kwan Yip
2021	J	`jnl`	Finite Temperature Cauchy-Born Rule and Stability of Crystalline Solids with Point Defects. Multiscale Model. Simul. Tao Luo, Yang Xiang, Jerry Zhijian Yang
2021	J	`jnl`	Linear Frequency Principle Model to Understand the Absence of Overfitting in Neural Networks. CoRR Yaoyu Zhang, Tao Luo, Zheng Ma, Zhi-Qin John Xu
2021	J	`jnl`	MOD-Net: A Machine Learning Approach via Model-Operator-Data Network for Solving PDEs. CoRR Lulu Zhang, Tao Luo, Yaoyu Zhang, Zhi-Qin John Xu, Zheng Ma
2021	J	`jnl`	Nonlinear Weighted Directed Acyclic Graph and A Priori Estimates for Neural Networks. CoRR Yuqing Li, Tao Luo, Chao Ma
2021	J	`jnl`	Phase Diagram for Two-layer ReLU Neural Networks at Infinite-width Limit. J. Mach. Learn. Res. Tao Luo, Zhi-Qin John Xu, Zheng Ma, Yaoyu Zhang
2021	J	`jnl`	Towards Understanding the Condensation of Two-layer Neural Networks at Initial Training. CoRR Zhi-Qin John Xu, Hanxu Zhou, Tao Luo, Yaoyu Zhang
2020	J	`jnl`	A regularized deep matrix factorized model of matrix completion for image restoration. CoRR Zhemin Li, Zhi-Qin John Xu, Tao Luo, Hongxia Wang
2020	—	`conf`	A type of generalization error induced by initialization in deep neural networks. MSML Yaoyu Zhang, Zhi-Qin John Xu, Tao Luo, Zheng Ma
2020	J	`jnl`	Fourier-domain Variational Formulation and Its Well-posedness for Supervised Learning. CoRR Tao Luo, Zheng Ma, Zhiwei Wang, Zhi-Qin John Xu, Yaoyu Zhang
2020	J	`jnl`	On the exact computation of linear frequency principle dynamics and its generalization. CoRR Tao Luo, Zheng Ma, Zhi-Qin John Xu, Yaoyu Zhang
2020	J	`jnl`	Phase diagram for two-layer ReLU neural networks at infinite-width limit. CoRR Tao Luo, Zhi-Qin John Xu, Zheng Ma, Yaoyu Zhang
2020	J	`jnl`	Towards an Understanding of Residual Networks Using Neural Tangent Hierarchy (NTH). CoRR Yuqing Li, Tao Luo, Nung Kwan Yip
2019	J	`jnl`	A type of generalization error induced by initialization in deep neural networks. CoRR Yaoyu Zhang, Zhi-Qin John Xu, Tao Luo, Zheng Ma
2019	J	`jnl`	Explicitizing an Implicit Bias of the Frequency Principle in Two-layer Neural Networks. CoRR Yaoyu Zhang, Zhi-Qin John Xu, Tao Luo, Zheng Ma
2019	J	`jnl`	Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks. CoRR Zhi-Qin John Xu, Yaoyu Zhang, Tao Luo, Yanyang Xiao, Zheng Ma
2019	J	`jnl`	Theory of the Frequency Principle for General Deep Neural Networks. CoRR Tao Luo, Zheng Ma, Zhi-Qin John Xu, Yaoyu Zhang
2016	J	`jnl`	Energy Scaling and Asymptotic Properties of Step Bunching in Epitaxial Growth with Elasticity Effects. Multiscale Model. Simul. Tao Luo, Yang Xiang, Nung Kwan Yip