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PFNN: A Penalty-Free Neural Network Method for Solving a Class of
  Second-Order Boundary-Value Problems on Complex Geometries

PFNN: A Penalty-Free Neural Network Method for Solving a Class of Second-Order Boundary-Value Problems on Complex Geometries

14 April 2020
H. Sheng
Chao Yang
ArXivPDFHTML

Papers citing "PFNN: A Penalty-Free Neural Network Method for Solving a Class of Second-Order Boundary-Value Problems on Complex Geometries"

9 / 9 papers shown
Title
Physics-informed solution reconstruction in elasticity and heat transfer using the explicit constraint force method
Physics-informed solution reconstruction in elasticity and heat transfer using the explicit constraint force method
Conor Rowan
K. Maute
Alireza Doostan
AI4CE
53
0
0
08 May 2025
Reliable and Efficient Inverse Analysis using Physics-Informed Neural Networks with Distance Functions and Adaptive Weight Tuning
Reliable and Efficient Inverse Analysis using Physics-Informed Neural Networks with Distance Functions and Adaptive Weight Tuning
Shota Deguchi
Mitsuteru Asai
PINN
AI4CE
81
0
0
25 Apr 2025
Bayesian identification of nonseparable Hamiltonians with multiplicative
  noise using deep learning and reduced-order modeling
Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling
Nicholas Galioto
Harsh Sharma
Boris Kramer
Alex Arkady Gorodetsky
44
0
0
23 Jan 2024
Machine learning and domain decomposition methods -- a survey
Machine learning and domain decomposition methods -- a survey
A. Klawonn
M. Lanser
J. Weber
AI4CE
24
7
0
21 Dec 2023
A Unified Hard-Constraint Framework for Solving Geometrically Complex
  PDEs
A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs
Songming Liu
Zhongkai Hao
Chengyang Ying
Hang Su
Jun Zhu
Ze Cheng
AI4CE
18
17
0
06 Oct 2022
DAS-PINNs: A deep adaptive sampling method for solving high-dimensional
  partial differential equations
DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations
Keju Tang
Xiaoliang Wan
Chao Yang
27
107
0
28 Dec 2021
Gradient-enhanced physics-informed neural networks for forward and
  inverse PDE problems
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems
Jeremy Yu
Lu Lu
Xuhui Meng
George Karniadakis
PINN
AI4CE
38
451
0
01 Nov 2021
Exact imposition of boundary conditions with distance functions in
  physics-informed deep neural networks
Exact imposition of boundary conditions with distance functions in physics-informed deep neural networks
N. Sukumar
Ankit Srivastava
PINN
AI4CE
52
241
0
17 Apr 2021
An overview on deep learning-based approximation methods for partial
  differential equations
An overview on deep learning-based approximation methods for partial differential equations
C. Beck
Martin Hutzenthaler
Arnulf Jentzen
Benno Kuckuck
30
146
0
22 Dec 2020
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