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Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in
  Scientific Computing

Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing

14 November 2022
Salah A. Faroughi
N. Pawar
C. Fernandes
Maziar Raissi
Subasish Das
N. Kalantari
S. K. Mahjour
    PINN
    AI4CE
ArXivPDFHTML

Papers citing "Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing"

26 / 26 papers shown
Title
Response Estimation and System Identification of Dynamical Systems via
  Physics-Informed Neural Networks
Response Estimation and System Identification of Dynamical Systems via Physics-Informed Neural Networks
M. Haywood-Alexander
Giacamo Arcieri
A. Kamariotis
Eleni Chatzi
21
1
0
02 Oct 2024
SGM-PINN: Sampling Graphical Models for Faster Training of
  Physics-Informed Neural Networks
SGM-PINN: Sampling Graphical Models for Faster Training of Physics-Informed Neural Networks
John Anticev
Ali Aghdaei
Wuxinlin Cheng
Zhuo Feng
AI4CE
26
0
0
10 Jul 2024
Physics-Enhanced Machine Learning: a position paper for dynamical
  systems investigations
Physics-Enhanced Machine Learning: a position paper for dynamical systems investigations
Alice Cicirello
PINN
AI4CE
24
7
0
08 May 2024
Stacked tensorial neural networks for reduced-order modeling of a
  parametric partial differential equation
Stacked tensorial neural networks for reduced-order modeling of a parametric partial differential equation
Caleb G. Wagner
9
0
0
21 Dec 2023
Discussing the Spectrum of Physics-Enhanced Machine Learning; a Survey
  on Structural Mechanics Applications
Discussing the Spectrum of Physics-Enhanced Machine Learning; a Survey on Structural Mechanics Applications
M. Haywood-Alexander
Wei Liu
Kiran Bacsa
Zhilu Lai
Eleni Chatzi
AI4CE
13
9
0
31 Oct 2023
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for
  Machine Learning and Process-based Hydrology
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology
Qingsong Xu
Yilei Shi
Jonathan Bamber
Ye Tuo
Ralf Ludwig
Xiao Xiang Zhu
AI4CE
18
9
0
08 Oct 2023
Bayesian Reasoning for Physics Informed Neural Networks
Bayesian Reasoning for Physics Informed Neural Networks
K. Graczyk
Kornel Witkowski
22
0
0
25 Aug 2023
A Domain-adaptive Physics-informed Neural Network for Inverse Problems
  of Maxwell's Equations in Heterogeneous Media
A Domain-adaptive Physics-informed Neural Network for Inverse Problems of Maxwell's Equations in Heterogeneous Media
Shiyuan Piao
Hong Gu
Aina Wang
Pan Qin
PINN
16
2
0
12 Aug 2023
Learning solution of nonlinear constitutive material models using
  physics-informed neural networks: COMM-PINN
Learning solution of nonlinear constitutive material models using physics-informed neural networks: COMM-PINN
Shahed Rezaei
Ahmad Moeineddin
Ali Harandi
PINN
12
17
0
10 Apr 2023
The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained
  Optimization: A Deep Learning Approach
The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach
Yongcun Song
Xiaoming Yuan
Hangrui Yue
PINN
22
6
0
16 Feb 2023
Towards Scalable Physically Consistent Neural Networks: an Application
  to Data-driven Multi-zone Thermal Building Models
Towards Scalable Physically Consistent Neural Networks: an Application to Data-driven Multi-zone Thermal Building Models
L. D. Natale
B. Svetozarevic
Philipp Heer
Colin N. Jones
AI4CE
8
26
0
23 Dec 2022
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
13
22
0
17 Dec 2022
Utilising physics-guided deep learning to overcome data scarcity
Utilising physics-guided deep learning to overcome data scarcity
Jinshuai Bai
Laith Alzubaidi
Qingxia Wang
E. Kuhl
Bennamoun
Yuantong T. Gu
PINN
AI4CE
19
3
0
24 Nov 2022
Physics-Informed Machine Learning: A Survey on Problems, Methods and
  Applications
Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications
Zhongkai Hao
Songming Liu
Yichi Zhang
Chengyang Ying
Yao Feng
Hang Su
Jun Zhu
PINN
AI4CE
21
87
0
15 Nov 2022
PhySRNet: Physics informed super-resolution network for application in
  computational solid mechanics
PhySRNet: Physics informed super-resolution network for application in computational solid mechanics
Rajat Arora
AI4CE
18
10
0
30 Jun 2022
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded
  Learning
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning
Chengping Rao
Pu Ren
Yang Liu
Hao-Lun Sun
AI4CE
28
26
0
28 Jan 2022
Enhancing Computational Fluid Dynamics with Machine Learning
Enhancing Computational Fluid Dynamics with Machine Learning
Ricardo Vinuesa
Steven L. Brunton
AI4CE
98
353
0
05 Oct 2021
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed
  Hermite-Spline CNNs
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed Hermite-Spline CNNs
Nils Wandel
Michael Weinmann
Michael Neidlin
Reinhard Klein
AI4CE
50
58
0
15 Sep 2021
Hard Encoding of Physics for Learning Spatiotemporal Dynamics
Hard Encoding of Physics for Learning Spatiotemporal Dynamics
Chengping Rao
Hao-Lun Sun
Yang Liu
PINN
AI4CE
27
9
0
02 May 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
69
220
0
26 Apr 2021
Machine Learning-Based Optimal Mesh Generation in Computational Fluid
  Dynamics
Machine Learning-Based Optimal Mesh Generation in Computational Fluid Dynamics
Keefe Huang
M. Krügener
Alistair Brown
F. Menhorn
H. Bungartz
D. Hartmann
AI4CE
20
24
0
25 Feb 2021
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
203
2,272
0
18 Oct 2020
Lagrangian Neural Networks
Lagrangian Neural Networks
M. Cranmer
S. Greydanus
Stephan Hoyer
Peter W. Battaglia
D. Spergel
S. Ho
PINN
121
419
0
10 Mar 2020
Symplectic Recurrent Neural Networks
Symplectic Recurrent Neural Networks
Zhengdao Chen
Jianyu Zhang
Martín Arjovsky
Léon Bottou
139
219
0
29 Sep 2019
Real-Time Single Image and Video Super-Resolution Using an Efficient
  Sub-Pixel Convolutional Neural Network
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
Wenzhe Shi
Jose Caballero
Ferenc Huszár
J. Totz
Andrew P. Aitken
Rob Bishop
Daniel Rueckert
Zehan Wang
SupR
190
5,163
0
16 Sep 2016
Convolutional LSTM Network: A Machine Learning Approach for
  Precipitation Nowcasting
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Xingjian Shi
Zhourong Chen
Hao Wang
Dit-Yan Yeung
W. Wong
W. Woo
201
7,884
0
13 Jun 2015
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