Wenjing Liao
Orcid: 0000-0003-2309-3839
According to our database1,
Wenjing Liao
authored at least 46 papers
between 2011 and 2024.
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Bibliography
2024
Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model Reduction for Operator Learning.
CoRR, 2024
CoRR, 2024
2023
Group Projected subspace pursuit for IDENTification of variable coefficient differential equations (GP-IDENT).
J. Comput. Phys., December, 2023
WeakIdent: Weak formulation for identifying differential equation using narrow-fit and trimming.
J. Comput. Phys., June, 2023
Group projected Subspace Pursuit for Identification of variable coefficient differential equations (GP-IDENT).
CoRR, 2023
Deep Nonparametric Estimation of Intrinsic Data Structures by Chart Autoencoders: Generalization Error and Robustness.
CoRR, 2023
Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories.
Proceedings of the International Conference on Machine Learning, 2023
2022
Stability and Super-Resolution of MUSIC and ESPRIT for Multi-Snapshot Spectral Estimation.
IEEE Trans. Signal Process., 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
WeakIdent: Weak formulation for Identifying Differential Equations using Narrow-fit and Trimming.
CoRR, 2022
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint.
CoRR, 2022
CoRR, 2022
CoRR, 2022
On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint.
Proceedings of the International Conference on Machine Learning, 2022
2021
IEEE Trans. Instrum. Meas., 2021
J. Sci. Comput., 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
Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks.
CoRR, 2020
Statistical Guarantees of Generative Adversarial Networks for Distribution Estimation.
CoRR, 2020
Gaussian noise removal with exponential functions and spectral norm of weighted Hankel matrices.
CoRR, 2020
2019
J. Mach. Learn. Res., 2019
CoRR, 2019
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
2018
Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018
Proceedings of the 24th IEEE International Conference on Parallel and Distributed Systems, 2018
2017
Stable super-resolution limit and smallest singular value of restricted Fourier matrices.
CoRR, 2017
2016
Learning adaptive multiscale approximations to data and functions near low-dimensional sets.
Proceedings of the 2016 IEEE Information Theory Workshop, 2016
2015
IEEE Trans. Signal Process., 2015
2014
CoRR, 2014
Proceedings of the 2014 IEEE Global Conference on Signal and Information Processing, 2014
Proceedings of the Web Technologies and Applications - 16th Asia-Pacific Web Conference, 2014
2013
LSSVM Network Flow Prediction Based on the Self-adaptive Genetic Algorithm Optimization.
J. Networks, 2013
2012
SIAM J. Imaging Sci., 2012
Proceedings of the Conference Record of the Forty Sixth Asilomar Conference on Signals, 2012
2011
Proceedings of the Conference Record of the Forty Fifth Asilomar Conference on Signals, 2011