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2111.01008
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HyperPINN: Learning parameterized differential equations with physics-informed hypernetworks
28 October 2021
Filipe de Avila Belbute-Peres
Yi-fan Chen
Fei Sha
PINN
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Papers citing
"HyperPINN: Learning parameterized differential equations with physics-informed hypernetworks"
10 / 10 papers shown
Title
Physics-informed neural networks for solving Reynolds-averaged Navier
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2013
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2013
Stokes equations
Hamidreza Eivazi
M. Tahani
P. Schlatter
Ricardo Vinuesa
PINN
AI4CE
62
267
0
22 Jul 2021
Active Training of Physics-Informed Neural Networks to Aggregate and Interpolate Parametric Solutions to the Navier-Stokes Equations
Christopher J. Arthurs
A. King
PINN
147
52
0
02 May 2020
A comparative study of physics-informed neural network models for learning unknown dynamics and constitutive relations
R. Tipireddy
P. Perdikaris
P. Stinis
A. Tartakovsky
PINN
66
34
0
02 Apr 2019
Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data
M. Raissi
A. Yazdani
George Karniadakis
AI4CE
PINN
90
161
0
13 Aug 2018
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
452
5,168
0
19 Jun 2018
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
M. Raissi
PINN
AI4CE
128
757
0
20 Jan 2018
Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems
M. Raissi
P. Perdikaris
George Karniadakis
PINN
152
266
0
04 Jan 2018
Neural networks catching up with finite differences in solving partial differential equations in higher dimensions
V. Avrutskiy
56
22
0
14 Dec 2017
DGM: A deep learning algorithm for solving partial differential equations
Justin A. Sirignano
K. Spiliopoulos
AI4CE
97
2,067
0
24 Aug 2017
HyperNetworks
David R Ha
Andrew M. Dai
Quoc V. Le
172
1,633
0
27 Sep 2016
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