Compressed sensing phase retrieval. - Albert Fannjiang; Wenjing Liao (ACSCC, 2011)

Mismatch and resolution in compressive imaging - Albert Fannjiang; Wenjing Liao (CoRR, 2011)

Super-resolution by compressive sensing algorithms. - Albert Fannjiang; Wenjing Liao (ACSCC, 2012)

Coherence Pattern-Guided Compressive Sensing with Unresolved Grids. - Albert Fannjiang; Wenjing Liao (SIAM J. Imaging Sci., 2012)

LSSVM Network Flow Prediction Based on the Self-adaptive Genetic Algorithm Optimization. - Wenjing Liao; Z. Balzen (J. Networks, 2013)

An Adaptive Skew Insensitive Join Algorithm for Large Scale Data Analytics. - Wenjing Liao; Tengjiao Wang 003; Hongyan Li 002; Dongqing Yang; Zhen Qiu; Kai Lei (APWeb, 2014)

MUSIC for joint frequency estimation: Stability with compressive measurements. - Wenjing Liao (GlobalSIP, 2014)

MUSIC for Single-Snapshot Spectral Estimation: Stability and Super-resolution. - Wenjing Liao; Albert Fannjiang (CoRR, 2014)

Ideal Code Constrained Supervised Sparse Coding. - Wenjing Liao; Robert Williams (J. Comput., 2014)

Contextual Patch Feature Learning for Face Recognition. - Wenjing Liao (J. Softw., 2014)

MUSIC for Multidimensional Spectral Estimation: Stability and Super-Resolution. - Wenjing Liao (IEEE Trans. Signal Process., 2015)

Learning adaptive multiscale approximations to data and functions near low-dimensional sets. - Wenjing Liao; Mauro Maggioni; Stefano Vigogna (ITW, 2016)

Sensor Calibration for Off-the-Grid Spectral Estimation. - Yonina C. Eldar; Wenjing Liao; Sui Tang (CoRR, 2017)

Stable super-resolution limit and smallest singular value of restricted Fourier matrices. - Weilin Li; Wenjing Liao (CoRR, 2017)

On the Tradeoff Between Data-Privacy and Utility for Data Publishing. - Wenjing Liao; Jianping He 001; Shanying Zhu; Cailian Chen; Xinping Guan (ICPADS, 2018)

A Non-Convex Approach To Joint Sensor Calibration And Spectrum Estimation. - Myung Cho; Wenjing Liao; Yuejie Chi (SSP, 2018)

Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds. - Minshuo Chen; Haoming Jiang; Wenjing Liao; Tuo Zhao (NeurIPS, 2019)

Conditioning of restricted Fourier matrices and super-resolution of MUSIC. - Weilin Li; Wenjing Liao (CoRR, 2019)

Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data. - Wenjing Liao; Mauro Maggioni (J. Mach. Learn. Res., 2019)

Gaussian noise removal with exponential functions and spectral norm of weighted Hankel matrices. - Tianyu Qiu; Wenjing Liao; Di Guo; Dongbao Liu; Xin Wang 105; Xiaobo Qu 001 (CoRR, 2020)

Statistical Guarantees of Generative Adversarial Networks for Distribution Estimation. - Minshuo Chen; Wenjing Liao; Hongyuan Zha; Tuo Zhao (CoRR, 2020)

Robust PDE Identification from Noisy Data. - Yuchen He 001; Sung Ha Kang; Wenjing Liao; Hao Liu 028; Yingjie Liu (CoRR, 2020)

Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks. - Minshuo Chen; Hao Liu 028; Wenjing Liao; Tuo Zhao (CoRR, 2020)

Super-Resolution Limit of the ESPRIT Algorithm. - Weilin Li; Wenjing Liao; Albert Fannjiang (IEEE Trans. Inf. Theory, 2020)

Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks. - Hao Liu 028; Minshuo Chen; Tuo Zhao; Wenjing Liao (ICML, 2021)

Multiscale regression on unknown manifolds. - Wenjing Liao; Mauro Maggioni; Stefano Vigogna (CoRR, 2021)

IDENT: Identifying Differential Equations with Numerical Time Evolution. - Sung Ha Kang; Wenjing Liao; Yingjie Liu (J. Sci. Comput., 2021)

An Automatic Denoising Method for NMR Spectroscopy Based on Low-Rank Hankel Model. - Tianyu Qiu; Wenjing Liao; Yihui Huang; Jinyu Wu; Di Guo; Dongbao Liu; Xin Wang 105; Jian-Feng Cai 001; Bingwen Hu; Xiaobo Qu 001 (IEEE Trans. Instrum. Meas., 2021)

Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. - Hao Liu 028; Minshuo Chen; Siawpeng Er; Wenjing Liao; Tong Zhang 001; Tuo Zhao (ICML, 2022)

On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds. - Biraj Dahal; Alexander Havrilla; Minshuo Chen; Tuo Zhao; Wenjing Liao (NeurIPS, 2022)

A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks. - Jie Wang 049; Minshuo Chen; Tuo Zhao; Wenjing Liao; Yao Xie 002 (CoRR, 2022)

Numerical Identification of Nonlocal Potential in Aggregation. - Yuchen He 001; Sung Ha Kang; Wenjing Liao; Hao Liu 028; Yingjie Liu (CoRR, 2022)

WeakIdent: Weak formulation for Identifying Differential Equations using Narrow-fit and Trimming. - Mengyi Tang; Wenjing Liao; Rachel Kuske; Sung Ha Kang (CoRR, 2022)

High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization. - Jiahui Cheng; Minshuo Chen; Hao Liu 028; Tuo Zhao; Wenjing Liao (CoRR, 2022)

Robust Identification of Differential Equations by Numerical Techniques from a Single Set of Noisy Observation. - Yuchen He 001; Sung Ha Kang; Wenjing Liao; Hao Liu 028; Yingjie Liu (SIAM J. Sci. Comput., 2022)

Stability and Super-Resolution of MUSIC and ESPRIT for Multi-Snapshot Spectral Estimation. - Weilin Li; Zengying Zhu; Weiguo Gao; Wenjing Liao (IEEE Trans. Signal Process., 2022)

Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories. - Zixuan Zhang; Minshuo Chen; Mengdi Wang; Wenjing Liao; Tuo Zhao (ICML, 2023)

Deep Nonparametric Estimation of Intrinsic Data Structures by Chart Autoencoders: Generalization Error and Robustness. - Hao Liu 028; Alexander Havrilla; Rongjie Lai; Wenjing Liao (CoRR, 2023)

Fourier Features for Identifying Differential Equations (FourierIdent). - Mengyi Tang; Hao Liu 028; Wenjing Liao; Sung Ha Kang (CoRR, 2023)

WeakIdent: Weak formulation for identifying differential equation using narrow-fit and trimming. - Mengyi Tang; Wenjing Liao; Rachel Kuske; Sung Ha Kang (J. Comput. Phys., 2023)

Group Projected subspace pursuit for IDENTification of variable coefficient differential equations (GP-IDENT). - Yuchen He 001; Sung Ha Kang; Wenjing Liao; Hao Liu 028; Yingjie Liu (J. Comput. Phys., 2023)

Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data. - Alexander Havrilla; Wenjing Liao (NeurIPS, 2024)

DFU: scale-robust diffusion model for zero-shot super-resolution image generation. - Alexander Havrilla; Kevin Rojas; Wenjing Liao; Molei Tao (CoRR, 2024)

Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model Reduction for Operator Learning. - Hao Liu 028; Biraj Dahal; Rongjie Lai; Wenjing Liao (CoRR, 2024)

Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation. - Hao Liu 028; Jiahui Cheng; Wenjing Liao (CoRR, 2024)

Neural Scaling Laws of Deep ReLU and Deep Operator Network: A Theoretical Study. - Hao Liu; Zecheng Zhang; Wenjing Liao; Hayden Schaeffer (CoRR, 2024)

Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces. - Hao Liu 028; Haizhao Yang; Minshuo Chen; Tuo Zhao; Wenjing Liao (J. Mach. Learn. Res., 2024)

Some notes on the basic concepts of support vector machines. - Yongping Wang; Wenjing Liao; Hongting Shen; Zilong Jiang; Jincheng Zhou (J. Comput. Sci., 2024)

Learning Functions Varying along a Central Subspace. - Hao Liu 028; Wenjing Liao (SIAM J. Math. Data Sci., 2024)

Coefficient-to-Basis Network: A Fine-Tunable Operator Learning Framework for Inverse Problems with Adaptive Discretizations and Theoretical Guarantees. - Zecheng Zhang; Hao Liu; Wenjing Liao; Guang Lin 001 (CoRR, 2025)

Optimality of Gradient-MUSIC for Spectral Estimation. - Albert Fannjiang; Weilin Li; Wenjing Liao (CoRR, 2025)

Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights. - Zhaiming Shen; Alex Havrilla; Rongjie Lai; Alexander Cloninger; Wenjing Liao (CoRR, 2025)

Single-shot prediction of parametric partial differential equations. - Khalid Rafiq; Wenjing Liao; Aditya G. Nair (CoRR, 2025)

Fresh agricultural products logistics network optimization incorporating departure time under the origin e-commerce model. - Qunli Yuchi; Wenjing Liao; Juhong Chen (Ann. Oper. Res., 2025)

Identification of Differential Equations by Dynamics-Guided Weighted Weak Form with Voting. - Jiahui Cheng; Sung Ha Kang; Haomin Zhou 001; Wenjing Liao (CoRR, 2025)

IDENT Review: Recent Advances in Identification of Differential Equations from Noisy Data. - Roy Y. He; Hao Liu; Wenjing Liao; Sung Ha Kang (CoRR, 2025)

Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods. - Zhaiming Shen; Alexander Hsu; Rongjie Lai; Wenjing Liao (CoRR, 2025)