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A Mathematical Guide to Operator Learning

A Mathematical Guide to Operator Learning

22 December 2023
Nicolas Boullé
Alex Townsend
ArXivPDFHTML

Papers citing "A Mathematical Guide to Operator Learning"

17 / 17 papers shown
Title
DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction
DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction
Rudy Morel
Jiequn Han
Edouard Oyallon
AI4CE
51
0
0
28 Apr 2025
Optimizing Hard Thresholding for Sparse Model Discovery
Optimizing Hard Thresholding for Sparse Model Discovery
Derek W. Jollie
Scott G. McCalla
41
0
0
28 Apr 2025
Uncertainty propagation in feed-forward neural network models
Uncertainty propagation in feed-forward neural network models
Jeremy Diamzon
Daniele Venturi
52
0
0
27 Mar 2025
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis
Yasamin Jalalian
Juan Felipe Osorio Ramirez
Alexander W. Hsu
Bamdad Hosseini
H. Owhadi
39
0
0
02 Mar 2025
An Advanced Physics-Informed Neural Operator for Comprehensive Design
  Optimization of Highly-Nonlinear Systems: An Aerospace Composites Processing
  Case Study
An Advanced Physics-Informed Neural Operator for Comprehensive Design Optimization of Highly-Nonlinear Systems: An Aerospace Composites Processing Case Study
Milad Ramezankhani
A. Deodhar
Rishi Parekh
Dagnachew Birru
AI4CE
33
3
0
20 Jun 2024
A finite element-based physics-informed operator learning framework for
  spatiotemporal partial differential equations on arbitrary domains
A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains
Yusuke Yamazaki
Ali Harandi
Mayu Muramatsu
A. Viardin
Markus Apel
T. Brepols
Stefanie Reese
Shahed Rezaei
AI4CE
26
12
0
21 May 2024
Hybrid Modeling Design Patterns
Hybrid Modeling Design Patterns
Maja Rudolph
Stefan Kurz
Barbara Rakitsch
AI4CE
11
6
0
29 Dec 2023
A Unified Framework to Enforce, Discover, and Promote Symmetry in
  Machine Learning
A Unified Framework to Enforce, Discover, and Promote Symmetry in Machine Learning
Samuel E. Otto
Nicholas Zolman
J. Nathan Kutz
Steven L. Brunton
AI4CE
25
11
0
01 Nov 2023
Neural Conservation Laws: A Divergence-Free Perspective
Neural Conservation Laws: A Divergence-Free Perspective
Jack Richter-Powell
Y. Lipman
Ricky T. Q. Chen
35
48
0
04 Oct 2022
Fourier Neural Operator with Learned Deformations for PDEs on General
  Geometries
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries
Zong-Yi Li
Daniel Zhengyu Huang
Burigede Liu
Anima Anandkumar
AI4CE
108
243
0
11 Jul 2022
Generic bounds on the approximation error for physics-informed (and)
  operator learning
Generic bounds on the approximation error for physics-informed (and) operator learning
Tim De Ryck
Siddhartha Mishra
PINN
59
58
0
23 May 2022
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLM
ALM
303
11,730
0
04 Mar 2022
Improved architectures and training algorithms for deep operator
  networks
Improved architectures and training algorithms for deep operator networks
Sifan Wang
Hanwen Wang
P. Perdikaris
AI4CE
42
102
0
04 Oct 2021
Multiwavelet-based Operator Learning for Differential Equations
Multiwavelet-based Operator Learning for Differential Equations
Gaurav Gupta
Xiongye Xiao
P. Bogdan
124
198
0
28 Sep 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
M. Bronstein
Joan Bruna
Taco S. Cohen
Petar Velivcković
GNN
166
1,095
0
27 Apr 2021
On the eigenvector bias of Fourier feature networks: From regression to
  solving multi-scale PDEs with physics-informed neural networks
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks
Sifan Wang
Hanwen Wang
P. Perdikaris
129
435
0
18 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
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