Liao, Wenjing

11 publications

ICLR 2026 Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods Zhaiming Shen, Alexander Hsu, Rongjie Lai, Wenjing Liao

JMLR 2025 Deep Neural Networks Are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation Hao Liu, Jiahui Cheng, Wenjing Liao

JMLR 2024 Deep Nonparametric Estimation of Operators Between Infinite Dimensional Spaces Hao Liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao

NeurIPS 2024 Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-Dimensional Data Alex Havrilla, Wenjing Liao

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

ICML 2022 Benefits of Overparameterized Convolutional Residual Networks: Function Approximation Under Smoothness Constraint Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao

NeurIPSW 2022 Benefits of Overparameterized Convolutional Residual Networks: Function Approximation Under Smoothness Constraint Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao

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

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

JMLR 2019 Adaptive Geometric Multiscale Approximations for Intrinsically Low-Dimensional Data Wenjing Liao, Mauro Maggioni

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