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Physics-informed Neural Networks for Solving Nonlinear Diffusivity and
  Biot's equations

Physics-informed Neural Networks for Solving Nonlinear Diffusivity and Biot's equations

19 February 2020
T. Kadeethum
T. Jørgensen
H. Nick
    PINN
    AI4CE
ArXivPDFHTML

Papers citing "Physics-informed Neural Networks for Solving Nonlinear Diffusivity and Biot's equations"

21 / 21 papers shown
Title
Efficient machine-learning surrogates for large-scale geological carbon
  and energy storage
Efficient machine-learning surrogates for large-scale geological carbon and energy storage
T. Kadeethum
Stephen J Verzi
Hongkyu Yoon
AI4CE
22
2
0
11 Oct 2023
Learning Generic Solutions for Multiphase Transport in Porous Media via
  the Flux Functions Operator
Learning Generic Solutions for Multiphase Transport in Porous Media via the Flux Functions Operator
W. Diab
Omar Chaabi
Shayma Alkobaisi
A. Awotunde
M. A. Kobaisi
AI4CE
21
2
0
03 Jul 2023
Temporal Consistency Loss for Physics-Informed Neural Networks
Temporal Consistency Loss for Physics-Informed Neural Networks
Sukirt Thakur
M. Raissi
H. Mitra
A. Ardekani
PINN
33
10
0
30 Jan 2023
Inverse modeling of nonisothermal multiphase poromechanics using
  physics-informed neural networks
Inverse modeling of nonisothermal multiphase poromechanics using physics-informed neural networks
Daniel Amini
E. Haghighat
R. Juanes
PINN
AI4CE
25
32
0
07 Sep 2022
Physics-informed neural network solution of thermo-hydro-mechanical
  (THM) processes in porous media
Physics-informed neural network solution of thermo-hydro-mechanical (THM) processes in porous media
Daniel Amini
E. Haghighat
R. Juanes
PINN
AI4CE
29
23
0
03 Mar 2022
State-of-the-Art Review of Design of Experiments for Physics-Informed
  Deep Learning
State-of-the-Art Review of Design of Experiments for Physics-Informed Deep Learning
Sourav Das
S. Tesfamariam
PINN
AI4CE
19
19
0
13 Feb 2022
Reduced order modeling for flow and transport problems with Barlow Twins
  self-supervised learning
Reduced order modeling for flow and transport problems with Barlow Twins self-supervised learning
T. Kadeethum
F. Ballarin
Daniel O’Malley
Youngsoo Choi
N. Bouklas
H. Yoon
AI4CE
27
17
0
11 Feb 2022
A coarse space acceleration of deep-DDM
A coarse space acceleration of deep-DDM
Valentin Mercier
Serge Gratton
Pierre Boudier
AI4CE
33
10
0
07 Dec 2021
Physics-informed neural network simulation of multiphase poroelasticity
  using stress-split sequential training
Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training
E. Haghighat
Daniel Amini
R. Juanes
PINN
AI4CE
23
95
0
06 Oct 2021
Deep Networks Provably Classify Data on Curves
Deep Networks Provably Classify Data on Curves
Tingran Wang
Sam Buchanan
D. Gilboa
John N. Wright
23
9
0
29 Jul 2021
Non-intrusive reduced order modeling of natural convection in porous
  media using convolutional autoencoders: comparison with linear subspace
  techniques
Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: comparison with linear subspace techniques
T. Kadeethum
F. Ballarin
Y. Cho
Daniel O’Malley
H. Yoon
N. Bouklas
AI4CE
18
61
0
23 Jul 2021
Interval and fuzzy physics-informed neural networks for uncertain fields
Interval and fuzzy physics-informed neural networks for uncertain fields
J. Fuhg
Ioannis Kalogeris
A. Fau
N. Bouklas
AI4CE
41
18
0
18 Jun 2021
A framework for data-driven solution and parameter estimation of PDEs
  using conditional generative adversarial networks
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks
T. Kadeethum
Daniel O’Malley
J. Fuhg
Youngsoo Choi
Jonghyun Lee
Hari S. Viswanathan
N. Bouklas
AI4CE
25
88
0
27 May 2021
Physics-informed attention-based neural network for solving non-linear
  partial differential equations
Physics-informed attention-based neural network for solving non-linear partial differential equations
R. Torrado
Pablo Ruiz
L. Cueto‐Felgueroso
M. Green
Tyler Friesen
S. Matringe
Julian Togelius
PINN
13
12
0
17 May 2021
The mixed deep energy method for resolving concentration features in
  finite strain hyperelasticity
The mixed deep energy method for resolving concentration features in finite strain hyperelasticity
J. Fuhg
N. Bouklas
PINN
AI4CE
28
90
0
15 Apr 2021
Non-intrusive reduced order modeling of poroelasticity of heterogeneous
  media based on a discontinuous Galerkin approximation
Non-intrusive reduced order modeling of poroelasticity of heterogeneous media based on a discontinuous Galerkin approximation
T. Kadeethum
F. Ballarin
N. Bouklas
AI4CE
53
26
0
28 Jan 2021
Meshless physics-informed deep learning method for three-dimensional
  solid mechanics
Meshless physics-informed deep learning method for three-dimensional solid mechanics
Diab W. Abueidda
Q. Lu
S. Koric
AI4CE
31
113
0
02 Dec 2020
Physics-informed neural networks for myocardial perfusion MRI
  quantification
Physics-informed neural networks for myocardial perfusion MRI quantification
R. L. M. V. Herten
A. Chiribiri
M. Breeuwer
M. Veta
C. Scannell
20
43
0
25 Nov 2020
Energy-based error bound of physics-informed neural network solutions in
  elasticity
Energy-based error bound of physics-informed neural network solutions in elasticity
Mengwu Guo
E. Haghighat
PINN
51
28
0
18 Oct 2020
Physics-informed Neural Networks for Solving Inverse Problems of
  Nonlinear Biot's Equations: Batch Training
Physics-informed Neural Networks for Solving Inverse Problems of Nonlinear Biot's Equations: Batch Training
T. Kadeethum
T. Jørgensen
H. Nick
PINN
AI4CE
19
19
0
18 May 2020
Active Training of Physics-Informed Neural Networks to Aggregate and
  Interpolate Parametric Solutions to the Navier-Stokes Equations
Active Training of Physics-Informed Neural Networks to Aggregate and Interpolate Parametric Solutions to the Navier-Stokes Equations
Christopher J. Arthurs
A. King
PINN
43
51
0
02 May 2020
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