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A practical existence theorem for reduced order models based on
  convolutional autoencoders

A practical existence theorem for reduced order models based on convolutional autoencoders

1 February 2024
N. R. Franco
Simone Brugiapaglia
    AI4CE
ArXivPDFHTML

Papers citing "A practical existence theorem for reduced order models based on convolutional autoencoders"

3 / 3 papers shown
Title
Deep Neural Networks Are Effective At Learning High-Dimensional
  Hilbert-Valued Functions From Limited Data
Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data
Ben Adcock
Simone Brugiapaglia
N. Dexter
S. Moraga
18
29
0
11 Dec 2020
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
203
2,254
0
18 Oct 2020
Hidden Unit Specialization in Layered Neural Networks: ReLU vs.
  Sigmoidal Activation
Hidden Unit Specialization in Layered Neural Networks: ReLU vs. Sigmoidal Activation
Elisa Oostwal
Michiel Straat
Michael Biehl
MLT
51
54
0
16 Oct 2019
1