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Finite basis Kolmogorov-Arnold networks: domain decomposition for
  data-driven and physics-informed problems

Finite basis Kolmogorov-Arnold networks: domain decomposition for data-driven and physics-informed problems

28 June 2024
Amanda A. Howard
Bruno Jacob
Sarah H. Murphy
Alexander Heinlein
P. Stinis
    AI4CE
ArXivPDFHTML

Papers citing "Finite basis Kolmogorov-Arnold networks: domain decomposition for data-driven and physics-informed problems"

11 / 11 papers shown
Title
Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks
Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks
Yihang Gao
Michael K. Ng
Vincent Y. F. Tan
66
0
0
17 Feb 2025
Sinc Kolmogorov-Arnold Network and Its Applications on Physics-informed
  Neural Networks
Sinc Kolmogorov-Arnold Network and Its Applications on Physics-informed Neural Networks
Tianchi Yu
Jingwei Qiu
Jiang Yang
Ivan V. Oseledets
18
2
0
05 Oct 2024
Kolmogorov-Arnold Network for Satellite Image Classification in Remote
  Sensing
Kolmogorov-Arnold Network for Satellite Image Classification in Remote Sensing
Minjong Cheon
31
42
0
02 Jun 2024
Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient
  Architecture for Nonlinear Function Approximation
Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient Architecture for Nonlinear Function Approximation
SS Sidharth
Keerthana AR
R. Gokul
Anas KP
51
72
0
12 May 2024
Stacked networks improve physics-informed training: applications to
  neural networks and deep operator networks
Stacked networks improve physics-informed training: applications to neural networks and deep operator networks
Amanda A. Howard
Sarah H. Murphy
Shady E. Ahmed
P. Stinis
AI4CE
47
18
0
11 Nov 2023
A multifidelity approach to continual learning for physical systems
A multifidelity approach to continual learning for physical systems
Amanda A. Howard
Yucheng Fu
P. Stinis
AI4CE
CLL
31
8
0
08 Apr 2023
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
37
102
0
04 Oct 2021
DAE-PINN: A Physics-Informed Neural Network Model for Simulating
  Differential-Algebraic Equations with Application to Power Networks
DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks
Christian Moya
Guang Lin
AI4CE
PINN
40
37
0
09 Sep 2021
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable
  domain decomposition approach for solving differential equations
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations
Benjamin Moseley
Andrew Markham
T. Nissen‐Meyer
PINN
37
206
0
16 Jul 2021
Efficient training of physics-informed neural networks via importance
  sampling
Efficient training of physics-informed neural networks via importance sampling
M. A. Nabian
R. J. Gladstone
Hadi Meidani
DiffM
PINN
57
218
0
26 Apr 2021
Parallel Physics-Informed Neural Networks via Domain Decomposition
Parallel Physics-Informed Neural Networks via Domain Decomposition
K. Shukla
Ameya Dilip Jagtap
George Karniadakis
PINN
88
214
0
20 Apr 2021
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