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Projection Methods for Operator Learning and Universal Approximation
v1v2v3 (latest)

Projection Methods for Operator Learning and Universal Approximation

18 June 2024
Emanuele Zappala
ArXiv (abs)PDFHTML

Papers citing "Projection Methods for Operator Learning and Universal Approximation"

5 / 5 papers shown
Title
Universal Approximation of Operators with Transformers and Neural Integral Operators
Universal Approximation of Operators with Transformers and Neural Integral Operators
E. Zappala
Maryam Bagherian
186
2
0
01 Sep 2024
Operator Learning: Algorithms and Analysis
Operator Learning: Algorithms and Analysis
Nikola B. Kovachki
S. Lanthaler
Andrew M. Stuart
417
67
0
24 Feb 2024
Spectral methods for Neural Integral Equations
Spectral methods for Neural Integral Equations
E. Zappala
119
2
0
09 Dec 2023
DeepONet: Learning nonlinear operators for identifying differential
  equations based on the universal approximation theorem of operators
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operatorsNature Machine Intelligence (NMI), 2019
Lu Lu
Pengzhan Jin
George Karniadakis
974
2,872
0
08 Oct 2019
The Expressive Power of Neural Networks: A View from the Width
The Expressive Power of Neural Networks: A View from the Width
Zhou Lu
Hongming Pu
Feicheng Wang
Zhiqiang Hu
Liwei Wang
448
962
0
08 Sep 2017
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