Hao Liu - RankMe

61 papers A* 2A 1Journal 56Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A PCA Based Model for Surface Reconstruction from Incomplete Point Clouds. SIAM J. Imaging Sci. Hao Liu
2026	J	`jnl`	Identifying Differential Equations in Fourier Domain (FourierIdent). J. Sci. Comput. Mengyi Tang, Hao Liu, Wenjing Liao, Sung Ha Kang
2026	J	`jnl`	WG-IDENT: Weak group identification of PDEs with varying coefficients. J. Comput. Phys. Cheng Tang, Roy Y. He, Hao Liu
2025	J	`jnl`	A Mathematical Explanation of Transformers for Large Language Models and GPTs. CoRR Xue-Cheng Tai, Hao Liu, Lingfeng Li, Raymond H. Chan
2025	J	`jnl`	A mathematical explanation of UNet. Math. Found. Comput. Xue-Cheng Tai, Hao Liu, Raymond H. Chan, Lingfeng Li
2025	J	`jnl`	Coefficient-to-Basis Network: A Fine-Tunable Operator Learning Framework for Inverse Problems with Adaptive Discretizations and Theoretical Guarantees. CoRR Zecheng Zhang, Hao Liu, Wenjing Liao, Guang Lin
2025	J	`jnl`	Data-Driven Model Reduction using WeldNet: Windowed Encoders for Learning Dynamics. CoRR Biraj Dahal, Jiahui Cheng, Hao Liu, Rongjie Lai, Wenjing Liao
2025	J	`jnl`	Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation. J. Mach. Learn. Res. Hao Liu, Jiahui Cheng, Wenjing Liao
2025	J	`jnl`	Deep convolutional neural networks meet variational shape compactness priors for image segmentation. Neurocomputing Kehui Zhang, Lingfeng Li, Hao Liu, Jing Yuan, Xue-Cheng Tai
2025	J	`jnl`	Fast Operator-Splitting Methods for Nonlinear Elliptic Equations. CoRR Jingyu Yang, Shingyu Leung, Jianliang Qian, Hao Liu
2025	J	`jnl`	Finite Element Representation Network (FERN) for Operator Learning with a Localized Trainable Basis. CoRR Zecheng Zhang, Hao Liu, Guosheng Fu, Hayden Schaeffer, Guang Lin
2025	J	`jnl`	IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data. CoRR Roy Y. He, Hao Liu, Wenjing Liao, Sung Ha Kang
2025	—	`conf`	Image Decomposition with G-Norm Weighted by Total Symmetric Variation. SSVM (2) Roy Y. He, Martin Huska, Hao Liu
2025	J	`jnl`	Image Decomposition with G-norm Weighted by Total Symmetric Variation. CoRR Roy Y. He, Martin Huska, Hao Liu
2025	—	`conf`	New Ways to Design Deep Neural Networks. NAIS Xue-Cheng Tai, Hao Liu, Chan H. Raymond, Lingfeng Li
2024	J	`jnl`	A Mathematical Explanation of UNet. CoRR Xue-Cheng Tai, Hao Liu, Raymond H. Chan, Lingfeng Li
2024	J	`jnl`	Deep Convolutional Neural Networks Meet Variational Shape Compactness Priors for Image Segmentation. CoRR Kehui Zhang, Lingfeng Li, Hao Liu, Jing Yuan, Xue-Cheng Tai
2024	J	`jnl`	Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation. CoRR Hao Liu, Jiahui Cheng, Wenjing Liao
2024	J	`jnl`	Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces. J. Mach. Learn. Res. Hao Liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao
2024	J	`jnl`	Double-Well Net for Image Segmentation. Multiscale Model. Simul. Hao Liu, Jun Liu, Raymond H. Chan, Xue-Cheng Tai
2024	J	`jnl`	Double-well Net for Image Segmentation. CoRR Hao Liu, Jun Liu, Raymond H. Chan, Xue-Cheng Tai
2024	J	`jnl`	Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model Reduction for Operator Learning. CoRR Hao Liu, Biraj Dahal, Rongjie Lai, Wenjing Liao
2024	J	`jnl`	Learning Functions Varying along a Central Subspace. SIAM J. Math. Data Sci. Hao Liu, Wenjing Liao
2024	J	`jnl`	Neural Scaling Laws of Deep ReLU and Deep Operator Network: A Theoretical Study. CoRR Hao Liu, Zecheng Zhang, Wenjing Liao, Hayden Schaeffer
2024	J	`jnl`	Operator-Splitting/Finite Element Methods for the Minkowski Problem. SIAM J. Sci. Comput. Hao Liu, Shingyu Leung, Jianliang Qian
2024	J	`jnl`	PottsMGNet: A Mathematical Explanation of Encoder-Decoder Based Neural Networks. SIAM J. Imaging Sci. Xue-Cheng Tai, Hao Liu, Raymond Chan
2023	J	`jnl`	Connections between Operator-splitting Methods and Deep Neural Networks with Applications in Image Segmentation. CoRR Hao Liu, Xue-Cheng Tai, Raymond H. Chan
2023	J	`jnl`	Deep Nonparametric Estimation of Intrinsic Data Structures by Chart Autoencoders: Generalization Error and Robustness. CoRR Hao Liu, Alexander Havrilla, Rongjie Lai, Wenjing Liao
2023	J	`jnl`	Elastica Models for Color Image Regularization. SIAM J. Imaging Sci. Hao Liu, Xue-Cheng Tai, Ron Kimmel, Roland Glowinski
2023	J	`jnl`	Fourier Features for Identifying Differential Equations (FourierIdent). CoRR Mengyi Tang, Hao Liu, Wenjing Liao, Sung Ha Kang
2023	J	`jnl`	Group Projected subspace pursuit for IDENTification of variable coefficient differential equations (GP-IDENT). J. Comput. Phys. Yuchen He, Sung Ha Kang, Wenjing Liao, Hao Liu, Yingjie Liu
2023	J	`jnl`	Group projected Subspace Pursuit for Identification of variable coefficient differential equations (GP-IDENT). CoRR Yuchen He, Sung Ha Kang, Wenjing Liao, Hao Liu, Yingjie Liu
2023	J	`jnl`	Operator Splitting/Finite Element Methods for the Minkowski Problem. CoRR Hao Liu, Shingyu Leung, Jianliang Qian
2023	J	`jnl`	PottsMGNet: A Mathematical Explanation of Encoder-Decoder Based Neural Networks. CoRR Xue-Cheng Tai, Hao Liu, Raymond H. Chan
2022	J	`jnl`	An Efficient Operator-Splitting Method for the Eigenvalue Problem of the Monge-Ampère Equation. CoRR Hao Liu, Shingyu Leung, Jianliang Qian
2022	J	`jnl`	An Operator-Splitting Method for the Gaussian Curvature Regularization Model with Applications to Surface Smoothing and Imaging. SIAM J. Sci. Comput. Hao Liu, Xue-Cheng Tai, Roland Glowinski
2022	A*	`conf`	Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. ICML Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao
2022	J	`jnl`	Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. CoRR Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao
2022	J	`jnl`	Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces. CoRR Hao Liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao
2022	J	`jnl`	Elastica Models for Color Image Regularization. CoRR Hao Liu, Xue-Cheng Tai, Ron Kimmel, Roland Glowinski
2022	J	`jnl`	High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization. CoRR Jiahui Cheng, Minshuo Chen, Hao Liu, Tuo Zhao, Wenjing Liao
2022	J	`jnl`	Numerical Identification of Nonlocal Potential in Aggregation. CoRR Yuchen He, Sung Ha Kang, Wenjing Liao, Hao Liu, Yingjie Liu
2022	J	`jnl`	Robust Identification of Differential Equations by Numerical Techniques from a Single Set of Noisy Observation. SIAM J. Sci. Comput. Yuchen He, Sung Ha Kang, Wenjing Liao, Hao Liu, Yingjie Liu
2021	J	`jnl`	A Color Elastica Model for Vector-Valued Image Regularization. SIAM J. Imaging Sci. Hao Liu, Xue-Cheng Tai, Ron Kimmel, Roland Glowinski
2021	J	`jnl`	An Operator-Splitting Method for the Gaussian Curvature Regularization Model with Applications in Surface Smoothing and Imaging. CoRR Hao Liu, Xue-Cheng Tai, Roland Glowinski
2021	A*	`conf`	Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks. ICML Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao
2021	J	`jnl`	Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks. CoRR Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao
2020	J	`jnl`	A Color Elastica Model for Vector-Valued Image Regularization. CoRR Hao Liu, Xue-Cheng Tai, Ron Kimmel, Roland Glowinski
2020	J	`jnl`	An Alternating Direction Explicit Method for Time Evolution Equations with Applications to Fractional Differential Equations. CoRR Hao Liu, Shingyu Leung
2020	J	`jnl`	Curvature Regularized Surface Reconstruction from Point Cloud. CoRR Yuchen He, Sung Ha Kang, Hao Liu
2020	J	`jnl`	Curvature Regularized Surface Reconstruction from Point Clouds. SIAM J. Imaging Sci. Yuchen He, Sung Ha Kang, Hao Liu
2020	J	`jnl`	Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks. CoRR Minshuo Chen, Hao Liu, Wenjing Liao, Tuo Zhao
2020	J	`jnl`	On the Numerical Solution of Nonlinear Eigenvalue Problems for the Monge-Ampère Operator. CoRR Roland Glowinski, Shingyu Leung, Hao Liu, Jianliang Qian
2020	J	`jnl`	Reinforcement Learning Tracking Control for Robotic Manipulator With Kernel-Based Dynamic Model. IEEE Trans. Neural Networks Learn. Syst. Yazhou Hu, Wenxue Wang, Hao Liu, Lianqing Liu
2020	J	`jnl`	Robust PDE Identification from Noisy Data. CoRR Yuchen He, Sung Ha Kang, Wenjing Liao, Hao Liu, Yingjie Liu
2019	J	`jnl`	A Finite Element/Operator-Splitting Method for the Numerical Solution of the Three Dimensional Monge-Ampère Equation. J. Sci. Comput. Hao Liu, Roland Glowinski, Shingyu Leung, Jianliang Qian
2019	J	`jnl`	A Finite Element/Operator-Splitting Method for the Numerical Solution of the Two Dimensional Elliptic Monge-Ampère Equation. J. Sci. Comput. Roland Glowinski, Hao Liu, Shingyu Leung, Jianliang Qian
2019	J	`jnl`	Correction to: A Finite Element/Operator-Splitting Method for the Numerical Solution of the Two Dimensional Elliptic Monge-Ampère Equation. J. Sci. Comput. Roland Glowinski, Hao Liu, Shingyu Leung, Jianliang Qian
2019	J	`jnl`	Fast Algorithms for Surface Reconstruction from Point Cloud. CoRR Yuchen He, Martin Huska, Sung Ha Kang, Hao Liu
2019	A	`conf`	Robotic Tracking Control with Kernel Trick-based Reinforcement Learning. IROS Yazhou Hu, Wenxue Wang, Hao Liu, Lianqing Liu
2017	J	`jnl`	A Level Set Based Variational Principal Flow Method for Nonparametric Dimension Reduction on Riemannian Manifolds. SIAM J. Sci. Comput. Hao Liu, Zhigang Yao, Shingyu Leung, Tony F. Chan