Nonparametric Regression on Low-Dimensional Manifolds using Deep ReLU
Networks : Function Approximation and Statistical Recovery

Nonparametric Regression on Low-Dimensional Manifolds using Deep ReLU Networks : Function Approximation and Statistical Recovery

5 August 2019

Papers citing "Nonparametric Regression on Low-Dimensional Manifolds using Deep ReLU Networks : Function Approximation and Statistical Recovery"

19 / 19 papers shown

Title
Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights Zhaiming Shen Alex Havrilla Rongjie Lai A. Cloninger Wenjing Liao 59 0 0 06 May 2025
Learning with Noisy Labels: the Exploration of Error Bounds in Classification Haixia Liu Boxiao Li Can Yang Yang Wang 51 0 0 28 Jan 2025
Deep Transfer Learning: Model Framework and Error Analysis Yuling Jiao Huazhen Lin Yuchen Luo Jerry Zhijian Yang 49 1 0 12 Oct 2024
On the optimal approximation of Sobolev and Besov functions using deep ReLU neural networks Yunfei Yang 72 2 0 02 Sep 2024
Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds Hong Ye Tan Subhadip Mukherjee Junqi Tang Carola-Bibiane Schönlieb 62 0 0 13 Aug 2024
Causal inference through multi-stage learning and doubly robust deep neural networks Yuqian Zhang Jelena Bradic OOD CML 42 0 0 11 Jul 2024
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning Arthur Jacot Seok Hoan Choi Yuxiao Wen AI4CE 96 2 0 08 Jul 2024
Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model Reduction for Operator Learning Hao Liu Biraj Dahal Rongjie Lai Wenjing Liao AI4CE 49 5 0 19 Jan 2024
Double-well Net for Image Segmentation Haotian Liu Jun Liu Raymond H. F. Chan Xue-Cheng Tai 73 7 0 31 Dec 2023
Color Image Recovery Using Generalized Matrix Completion over Higher-Order Finite Dimensional Algebra L. Liao Zhuang Guo Qi Gao Yan Wang Fajun Yu Qifeng Zhao Stephen J. Maybank 23 55 0 04 Aug 2023
Deep Nonparametric Estimation of Intrinsic Data Structures by Chart Autoencoders: Generalization Error and Robustness Hao Liu Alex Havrilla Rongjie Lai Wenjing Liao 54 6 0 17 Mar 2023
Intrinsic and extrinsic deep learning on manifolds Yi-Zheng Fang Ilsang Ohn Vijay Gupta Lizhen Lin 18 2 0 16 Feb 2023
Deep Operator Learning Lessens the Curse of Dimensionality for PDEs Ke Chen Chunmei Wang Haizhao Yang AI4CE 47 13 0 28 Jan 2023
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD Alireza Mousavi-Hosseini Sejun Park M. Girotti Ioannis Mitliagkas Murat A. Erdogdu MLT 324 48 0 29 Sep 2022
Fitting an immersed submanifold to data via Sussmann's orbit theorem Joshua Hanson Maxim Raginsky 33 4 0 03 Apr 2022
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces Hao Liu Haizhao Yang Minshuo Chen T. Zhao Wenjing Liao 54 37 0 01 Jan 2022
A Deep Generative Approach to Conditional Sampling Xingyu Zhou Yuling Jiao Jin Liu Jian Huang 20 42 0 19 Oct 2021
Deep Networks Provably Classify Data on Curves Tingran Wang Sam Buchanan D. Gilboa John N. Wright 28 9 0 29 Jul 2021
Deep Nonparametric Regression on Approximate Manifolds: Non-Asymptotic Error Bounds with Polynomial Prefactors Yuling Jiao Guohao Shen Yuanyuan Lin Jian Huang 66 50 0 14 Apr 2021