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Deep Nonparametric Estimation of Intrinsic Data Structures by Chart
  Autoencoders: Generalization Error and Robustness

Deep Nonparametric Estimation of Intrinsic Data Structures by Chart Autoencoders: Generalization Error and Robustness

17 March 2023
Hao Liu
Alex Havrilla
Rongjie Lai
Wenjing Liao
ArXivPDFHTML

Papers citing "Deep Nonparametric Estimation of Intrinsic Data Structures by Chart Autoencoders: Generalization Error and Robustness"

5 / 5 papers shown
Title
Neural Scaling Laws of Deep ReLU and Deep Operator Network: A
  Theoretical Study
Neural Scaling Laws of Deep ReLU and Deep Operator Network: A Theoretical Study
Hao Liu
Zecheng Zhang
Wenjing Liao
Hayden Schaeffer
21
1
0
01 Oct 2024
A Statistical Analysis of Wasserstein Autoencoders for Intrinsically
  Low-dimensional Data
A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data
Saptarshi Chakraborty
Peter L. Bartlett
31
1
0
24 Feb 2024
Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model
  Reduction for Operator Learning
Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model Reduction for Operator Learning
Hao Liu
Biraj Dahal
Rongjie Lai
Wenjing Liao
AI4CE
21
4
0
19 Jan 2024
Connections between Operator-splitting Methods and Deep Neural Networks
  with Applications in Image Segmentation
Connections between Operator-splitting Methods and Deep Neural Networks with Applications in Image Segmentation
Hao Liu
X. Tai
Raymond H. F. Chan
16
3
0
18 Jul 2023
The Intrinsic Dimension of Images and Its Impact on Learning
The Intrinsic Dimension of Images and Its Impact on Learning
Phillip E. Pope
Chen Zhu
Ahmed Abdelkader
Micah Goldblum
Tom Goldstein
189
256
0
18 Apr 2021
1