Hao Liu
Orcid: 0000-0002-7504-9859Affiliations:
- Hong Kong Baptist University, Department of Mathematics, Hong Kong
- Georgia Institute of Technology, Department of Mathematics, Atlanta, GA, USA (former)
- Hong Kong University of Science and Technology, Department of Mathematics, Hong Kong (former)
According to our database1,
Hao Liu
authored at least 36 papers
between 2017 and 2024.
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Bibliography
2024
SIAM J. Imaging Sci., March, 2024
SIAM J. Sci. Comput., 2024
J. Mach. Learn. Res., 2024
Deep Convolutional Neural Networks Meet Variational Shape Compactness Priors for Image Segmentation.
CoRR, 2024
Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation.
CoRR, 2024
Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model Reduction for Operator Learning.
CoRR, 2024
2023
Group Projected subspace pursuit for IDENTification of variable coefficient differential equations (GP-IDENT).
J. Comput. Phys., December, 2023
Connections between Operator-splitting Methods and Deep Neural Networks with Applications in Image Segmentation.
CoRR, 2023
Deep Nonparametric Estimation of Intrinsic Data Structures by Chart Autoencoders: Generalization Error and Robustness.
CoRR, 2023
2022
An Operator-Splitting Method for the Gaussian Curvature Regularization Model with Applications to Surface Smoothing and Imaging.
SIAM J. Sci. Comput., 2022
Robust Identification of Differential Equations by Numerical Techniques from a Single Set of Noisy Observation.
SIAM J. Sci. Comput., 2022
High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization.
CoRR, 2022
An Efficient Operator-Splitting Method for the Eigenvalue Problem of the Monge-Ampère Equation.
CoRR, 2022
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint.
Proceedings of the International Conference on Machine Learning, 2022
2021
SIAM J. Imaging Sci., 2021
An Operator-Splitting Method for the Gaussian Curvature Regularization Model with Applications in Surface Smoothing and Imaging.
CoRR, 2021
Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
Reinforcement Learning Tracking Control for Robotic Manipulator With Kernel-Based Dynamic Model.
IEEE Trans. Neural Networks Learn. Syst., 2020
SIAM J. Imaging Sci., 2020
Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks.
CoRR, 2020
On the Numerical Solution of Nonlinear Eigenvalue Problems for the Monge-Ampère Operator.
CoRR, 2020
An Alternating Direction Explicit Method for Time Evolution Equations with Applications to Fractional Differential Equations.
CoRR, 2020
2019
A Finite Element/Operator-Splitting Method for the Numerical Solution of the Three Dimensional Monge-Ampère Equation.
J. Sci. Comput., 2019
Correction to: A Finite Element/Operator-Splitting Method for the Numerical Solution of the Two Dimensional Elliptic Monge-Ampère Equation.
J. Sci. Comput., 2019
A Finite Element/Operator-Splitting Method for the Numerical Solution of the Two Dimensional Elliptic Monge-Ampère Equation.
J. Sci. Comput., 2019
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019
2017
A Level Set Based Variational Principal Flow Method for Nonparametric Dimension Reduction on Riemannian Manifolds.
SIAM J. Sci. Comput., 2017