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A deep network construction that adapts to intrinsic dimensionality
  beyond the domain

A deep network construction that adapts to intrinsic dimensionality beyond the domain

6 August 2020
A. Cloninger
T. Klock
    AI4CE
ArXivPDFHTML

Papers citing "A deep network construction that adapts to intrinsic dimensionality beyond the domain"

4 / 4 papers shown
Title
Deep Operator Learning Lessens the Curse of Dimensionality for PDEs
Deep Operator Learning Lessens the Curse of Dimensionality for PDEs
Ke Chen
Chunmei Wang
Haizhao Yang
AI4CE
24
13
0
28 Jan 2023
On the Geometry of Reinforcement Learning in Continuous State and Action
  Spaces
On the Geometry of Reinforcement Learning in Continuous State and Action Spaces
Saket Tiwari
Omer Gottesman
George Konidaris
26
0
0
29 Dec 2022
Effects of Data Geometry in Early Deep Learning
Effects of Data Geometry in Early Deep Learning
Saket Tiwari
George Konidaris
82
7
0
29 Dec 2022
Deep Nonparametric Estimation of Operators between Infinite Dimensional
  Spaces
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces
Hao Liu
Haizhao Yang
Minshuo Chen
T. Zhao
Wenjing Liao
32
36
0
01 Jan 2022
1