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Critical Investigation of Failure Modes in Physics-informed Neural
  Networks

Critical Investigation of Failure Modes in Physics-informed Neural Networks

20 June 2022
S. Basir
Inanc Senocak
    PINN
    AI4CE
ArXivPDFHTML

Papers citing "Critical Investigation of Failure Modes in Physics-informed Neural Networks"

13 / 13 papers shown
Title
Unraveling particle dark matter with Physics-Informed Neural Networks
Unraveling particle dark matter with Physics-Informed Neural Networks
M.P. Bento
H.B. Câmara
J.F. Seabra
90
0
0
24 Feb 2025
Gaussian Variational Schemes on Bounded and Unbounded Domains
Gaussian Variational Schemes on Bounded and Unbounded Domains
Jonas A. Actor
Anthony Gruber
E. Cyr
Nathaniel Trask
48
0
0
08 Oct 2024
Beyond Derivative Pathology of PINNs: Variable Splitting Strategy with
  Convergence Analysis
Beyond Derivative Pathology of PINNs: Variable Splitting Strategy with Convergence Analysis
Yesom Park
Changhoon Song
Myungjoo Kang
33
2
0
30 Sep 2024
Robust Neural IDA-PBC: passivity-based stabilization under
  approximations
Robust Neural IDA-PBC: passivity-based stabilization under approximations
Santiago Sanchez-Escalonilla
Samuele Zoboli
B. Jayawardhana
50
1
0
24 Sep 2024
BiLO: Bilevel Local Operator Learning for PDE inverse problems
BiLO: Bilevel Local Operator Learning for PDE inverse problems
Ray Zirui Zhang
Xiaohui Xie
John S. Lowengrub
73
2
0
27 Apr 2024
PARCv2: Physics-aware Recurrent Convolutional Neural Networks for
  Spatiotemporal Dynamics Modeling
PARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling
Phong C. H. Nguyen
Xinlun Cheng
Shahab Azarfar
P. Seshadri
Y. Nguyen
Munho Kim
Sanghun Choi
H. Udaykumar
Stephen Seung-Yeob Baek
AI4CE
PINN
50
1
0
19 Feb 2024
Architectural Strategies for the optimization of Physics-Informed Neural
  Networks
Architectural Strategies for the optimization of Physics-Informed Neural Networks
Hemanth Saratchandran
Shin-Fang Chng
Simon Lucey
AI4CE
48
0
0
05 Feb 2024
Approximating Numerical Fluxes Using Fourier Neural Operators for
  Hyperbolic Conservation Laws
Approximating Numerical Fluxes Using Fourier Neural Operators for Hyperbolic Conservation Laws
Taeyoung Kim
Myungjoo Kang
AI4CE
30
3
0
03 Jan 2024
An adaptive augmented Lagrangian method for training physics and
  equality constrained artificial neural networks
An adaptive augmented Lagrangian method for training physics and equality constrained artificial neural networks
S. Basir
Inanc Senocak
PINN
29
5
0
08 Jun 2023
ParticleWNN: a Novel Neural Networks Framework for Solving Partial
  Differential Equations
ParticleWNN: a Novel Neural Networks Framework for Solving Partial Differential Equations
Yaohua Zang
Gang Bao
51
4
0
21 May 2023
Investigating and Mitigating Failure Modes in Physics-informed Neural
  Networks (PINNs)
Investigating and Mitigating Failure Modes in Physics-informed Neural Networks (PINNs)
S. Basir
PINN
AI4CE
38
22
0
20 Sep 2022
Characterizing and Mitigating the Difficulty in Training
  Physics-informed Artificial Neural Networks under Pointwise Constraints
Characterizing and Mitigating the Difficulty in Training Physics-informed Artificial Neural Networks under Pointwise Constraints
S. Basir
Inanc Senocak
AI4CE
47
1
0
19 Jun 2022
Lagrangian PINNs: A causality-conforming solution to failure modes of
  physics-informed neural networks
Lagrangian PINNs: A causality-conforming solution to failure modes of physics-informed neural networks
R. Mojgani
Maciej Balajewicz
Pedram Hassanzadeh
PINN
43
45
0
05 May 2022
1