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Physics and geometry informed neural operator network with application
  to acoustic scattering

Physics and geometry informed neural operator network with application to acoustic scattering

2 June 2024
S. Nair
Timothy F. Walsh
Greg Pickrell
Fabio Semperlotti
    AI4CE
ArXivPDFHTML

Papers citing "Physics and geometry informed neural operator network with application to acoustic scattering"

11 / 11 papers shown
Title
DeepONet-Grid-UQ: A Trustworthy Deep Operator Framework for Predicting
  the Power Grid's Post-Fault Trajectories
DeepONet-Grid-UQ: A Trustworthy Deep Operator Framework for Predicting the Power Grid's Post-Fault Trajectories
Christian Moya
Shiqi Zhang
Meng Yue
Guang Lin
50
43
0
15 Feb 2022
Simulating progressive intramural damage leading to aortic dissection
  using an operator-regression neural network
Simulating progressive intramural damage leading to aortic dissection using an operator-regression neural network
Minglang Yin
Ehsan Ban
B. Rego
Enrui Zhang
C. Cavinato
J. Humphrey
George Karniadakis
AI4CE
61
53
0
25 Aug 2021
Learning the solution operator of parametric partial differential
  equations with physics-informed DeepOnets
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets
Sizhuang He
Hanwen Wang
P. Perdikaris
AI4CE
75
695
0
19 Mar 2021
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
87
512
0
09 Feb 2021
A Physics-Informed Machine Learning Approach for Solving Heat Transfer
  Equation in Advanced Manufacturing and Engineering Applications
A Physics-Informed Machine Learning Approach for Solving Heat Transfer Equation in Advanced Manufacturing and Engineering Applications
N. Zobeiry
K. D. Humfeld
AI4CE
50
272
0
28 Sep 2020
Active learning of deep surrogates for PDEs: Application to metasurface
  design
Active learning of deep surrogates for PDEs: Application to metasurface design
R. Pestourie
Youssef Mroueh
Thanh V. Nguyen
Payel Das
Steven G. Johnson
AI4CE
45
73
0
24 Aug 2020
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 operators
Lu Lu
Pengzhan Jin
George Karniadakis
200
2,108
0
08 Oct 2019
Physical Symmetries Embedded in Neural Networks
Physical Symmetries Embedded in Neural Networks
M. Mattheakis
P. Protopapas
D. Sondak
Marco Di Giovanni
E. Kaxiras
PINN
41
71
0
18 Apr 2019
Data Driven Governing Equations Approximation Using Deep Neural Networks
Data Driven Governing Equations Approximation Using Deep Neural Networks
Tong Qin
Kailiang Wu
D. Xiu
PINN
62
272
0
13 Nov 2018
Inception-v4, Inception-ResNet and the Impact of Residual Connections on
  Learning
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Christian Szegedy
Sergey Ioffe
Vincent Vanhoucke
Alexander A. Alemi
350
14,223
0
23 Feb 2016
Automatic differentiation in machine learning: a survey
Automatic differentiation in machine learning: a survey
A. G. Baydin
Barak A. Pearlmutter
Alexey Radul
J. Siskind
PINN
AI4CE
ODL
148
2,796
0
20 Feb 2015
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