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Hyper-parameter tuning of physics-informed neural networks: Application
  to Helmholtz problems

Hyper-parameter tuning of physics-informed neural networks: Application to Helmholtz problems

13 May 2022
Paul Escapil-Inchauspé
G. A. Ruz
ArXivPDFHTML

Papers citing "Hyper-parameter tuning of physics-informed neural networks: Application to Helmholtz problems"

6 / 6 papers shown
Title
A physics-informed transformer neural operator for learning generalized solutions of initial boundary value problems
A physics-informed transformer neural operator for learning generalized solutions of initial boundary value problems
Sumanth Kumar Boya
Deepak Subramani
AI4CE
94
0
0
12 Dec 2024
Error convergence and engineering-guided hyperparameter search of PINNs:
  towards optimized I-FENN performance
Error convergence and engineering-guided hyperparameter search of PINNs: towards optimized I-FENN performance
Panos Pantidis
Habiba Eldababy
Christopher Miguel Tagle
M. Mobasher
32
20
0
03 Mar 2023
h-analysis and data-parallel physics-informed neural networks
h-analysis and data-parallel physics-informed neural networks
Paul Escapil-Inchauspé
G. A. Ruz
PINN
AI4CE
29
2
0
17 Feb 2023
Physics-informed Neural Networks with Periodic Activation Functions for
  Solute Transport in Heterogeneous Porous Media
Physics-informed Neural Networks with Periodic Activation Functions for Solute Transport in Heterogeneous Porous Media
Salah A. Faroughi
Ramin Soltanmohammad
Pingki Datta
S. K. Mahjour
S. Faroughi
15
22
0
17 Dec 2022
Physics-informed neural networks for operator equations with stochastic
  data
Physics-informed neural networks for operator equations with stochastic data
Paul Escapil-Inchauspé
G. A. Ruz
29
2
0
15 Nov 2022
Physics-informed neural networks with hard constraints for inverse
  design
Physics-informed neural networks with hard constraints for inverse design
Lu Lu
R. Pestourie
Wenjie Yao
Zhicheng Wang
F. Verdugo
Steven G. Johnson
PINN
39
494
0
09 Feb 2021
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