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When and why PINNs fail to train: A neural tangent kernel perspective

When and why PINNs fail to train: A neural tangent kernel perspective

28 July 2020
Sifan Wang
Xinling Yu
P. Perdikaris
ArXivPDFHTML

Papers citing "When and why PINNs fail to train: A neural tangent kernel perspective"

50 / 336 papers shown
Title
Anant-Net: Breaking the Curse of Dimensionality with Scalable and Interpretable Neural Surrogate for High-Dimensional PDEs
Anant-Net: Breaking the Curse of Dimensionality with Scalable and Interpretable Neural Surrogate for High-Dimensional PDEs
Sidharth S. Menon
Ameya D. Jagtap
PINN
104
0
0
06 May 2025
Physics-informed neural network estimation of active material properties in time-dependent cardiac biomechanical models
Physics-informed neural network estimation of active material properties in time-dependent cardiac biomechanical models
Matthias Höfler
Francesco Regazzoni
S. Pagani
Elias Karabelas
Christoph M. Augustin
Gundolf Haase
Gernot Plank
Federica Caforio
22
0
0
06 May 2025
Reduced-order structure-property linkages for stochastic metamaterials
Reduced-order structure-property linkages for stochastic metamaterials
Hooman Danesh
Maruthi Annamaraju
T. Brepols
Stefanie Reese
Surya R. Kalidindi
22
0
0
02 May 2025
Integration Matters for Learning PDEs with Backwards SDEs
Integration Matters for Learning PDEs with Backwards SDEs
Sungje Park
Stephen Tu
PINN
50
0
0
02 May 2025
Multi-level datasets training method in Physics-Informed Neural Networks
Multi-level datasets training method in Physics-Informed Neural Networks
Yao-Hsuan Tsai
Hsiao-Tung Juan
Pao-Hsiung Chiu
Chao-An Lin
AI4CE
36
0
0
30 Apr 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
76
0
0
25 Apr 2025
Equilibrium Conserving Neural Operators for Super-Resolution Learning
Equilibrium Conserving Neural Operators for Super-Resolution Learning
Vivek Oommen
Andreas E. Robertson
Daniel Diaz
Coleman Alleman
Zhen Zhang
Anthony D. Rollett
George Karniadakis
Rémi Dingreville
33
1
0
18 Apr 2025
How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings
How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings
Samuel Audia
S. Feizi
Matthias Zwicker
Dinesh Manocha
23
0
0
18 Apr 2025
Physics Informed Constrained Learning of Dynamics from Static Data
Physics Informed Constrained Learning of Dynamics from Static Data
Pengtao Dang
Tingbo Guo
Melissa Fishel
Guang Lin
Wenzhuo Wu
Sha Cao
Chi Zhang
PINN
AI4CE
49
0
0
17 Apr 2025
RL-PINNs: Reinforcement Learning-Driven Adaptive Sampling for Efficient Training of PINNs
RL-PINNs: Reinforcement Learning-Driven Adaptive Sampling for Efficient Training of PINNs
Zhenao Song
23
0
0
17 Apr 2025
BO-SA-PINNs: Self-adaptive physics-informed neural networks based on Bayesian optimization for automatically designing PDE solvers
BO-SA-PINNs: Self-adaptive physics-informed neural networks based on Bayesian optimization for automatically designing PDE solvers
Rui Zhang
Liang Li
Stéphane Lanteri
Hao Kang
Jiaqi Li
29
0
0
14 Apr 2025
Hybrid Temporal Differential Consistency Autoencoder for Efficient and Sustainable Anomaly Detection in Cyber-Physical Systems
Hybrid Temporal Differential Consistency Autoencoder for Efficient and Sustainable Anomaly Detection in Cyber-Physical Systems
Michael Somma
AI4CE
16
0
0
08 Apr 2025
PINNverse: Accurate parameter estimation in differential equations from noisy data with constrained physics-informed neural networks
PINNverse: Accurate parameter estimation in differential equations from noisy data with constrained physics-informed neural networks
Marius Almanstötter
Roman Vetter
Dagmar Iber
PINN
32
1
0
07 Apr 2025
Provably accurate adaptive sampling for collocation points in physics-informed neural networks
Provably accurate adaptive sampling for collocation points in physics-informed neural networks
Antoine Caradot
Rémi Emonet
Amaury Habrard
Abdel-Rahim Mezidi
M. Sebban
39
0
0
01 Apr 2025
Hard-constraining Neumann boundary conditions in physics-informed neural networks via Fourier feature embeddings
Hard-constraining Neumann boundary conditions in physics-informed neural networks via Fourier feature embeddings
Christopher Straub
Philipp Brendel
Vlad Medvedev
A. Rosskopf
36
0
0
01 Apr 2025
A discrete physics-informed training for projection-based reduced order models with neural networks
A discrete physics-informed training for projection-based reduced order models with neural networks
N. Sibuet
S. A. D. Parga
J. R. Bravo
R. Rossi
29
0
0
31 Mar 2025
Integral regularization PINNs for evolution equations
Integral regularization PINNs for evolution equations
Xiaodong Feng
Haojiong Shangguan
Tao Tang
Xiaoliang Wan
PINN
57
0
0
31 Mar 2025
Enhancing Physics-Informed Neural Networks with a Hybrid Parallel Kolmogorov-Arnold and MLP Architecture
Enhancing Physics-Informed Neural Networks with a Hybrid Parallel Kolmogorov-Arnold and MLP Architecture
Zuyu Xu
Bin Lv
39
0
0
30 Mar 2025
F-INR: Functional Tensor Decomposition for Implicit Neural Representations
F-INR: Functional Tensor Decomposition for Implicit Neural Representations
Sai Karthikeya Vemuri
Tim Buchner
Joachim Denzler
AI4CE
39
0
0
27 Mar 2025
Neural Tangent Kernel of Neural Networks with Loss Informed by Differential Operators
Weiye Gan
Yicheng Li
Q. Lin
Zuoqiang Shi
34
0
0
14 Mar 2025
Challenges and Advancements in Modeling Shock Fronts with Physics-Informed Neural Networks: A Review and Benchmarking Study
Challenges and Advancements in Modeling Shock Fronts with Physics-Informed Neural Networks: A Review and Benchmarking Study
J. Abbasi
Ameya D. Jagtap
Ben Moseley
Aksel Hiorth
P. Andersen
PINN
AI4CE
39
1
0
14 Mar 2025
Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout
Bharat Srikishan
Daniel O'Malley
Mohamed Mehana
Nicholas Lubbers
Nikhil Muralidhar
AI4CE
45
0
0
13 Mar 2025
PIED: Physics-Informed Experimental Design for Inverse Problems
Apivich Hemachandra
Gregory Kang Ruey Lau
S. Ng
Bryan Kian Hsiang Low
PINN
42
0
0
10 Mar 2025
Parametric Value Approximation for General-sum Differential Games with State Constraints
Lei Zhang
Mukesh Ghimire
Wenlong Zhang
Z. Xu
Yi Ren
36
0
0
10 Mar 2025
Make Haste Slowly: A Theory of Emergent Structured Mixed Selectivity in Feature Learning ReLU Networks
Make Haste Slowly: A Theory of Emergent Structured Mixed Selectivity in Feature Learning ReLU Networks
Devon Jarvis
Richard Klein
Benjamin Rosman
Andrew M. Saxe
MLT
64
1
0
08 Mar 2025
Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble
Zongren Zou
Zhicheng Wang
George Karniadakis
PINN
AI4CE
65
2
0
08 Mar 2025
REAct: Rational Exponential Activation for Better Learning and Generalization in PINNs
Sourav Mishra
Shreya Hallikeri
Suresh Sundaram
AI4CE
36
0
0
04 Mar 2025
Physics-Informed Neural Networks for Optimal Vaccination Plan in SIR Epidemic Models
Physics-Informed Neural Networks for Optimal Vaccination Plan in SIR Epidemic Models
Minseok Kim
Yeongjong Kim
Yeoneung Kim
PINN
83
0
0
27 Feb 2025
Anomaly Detection in Complex Dynamical Systems: A Systematic Framework Using Embedding Theory and Physics-Inspired Consistency
Anomaly Detection in Complex Dynamical Systems: A Systematic Framework Using Embedding Theory and Physics-Inspired Consistency
Michael Somma
Thomas Gallien
Branka Stojanovic
AI4CE
56
1
0
26 Feb 2025
Exact Learning of Permutations for Nonzero Binary Inputs with Logarithmic Training Size and Quadratic Ensemble Complexity
George Giapitzakis
Artur Back de Luca
K. Fountoulakis
54
0
0
24 Feb 2025
Gradient Alignment in Physics-informed Neural Networks: A Second-Order Optimization Perspective
Gradient Alignment in Physics-informed Neural Networks: A Second-Order Optimization Perspective
Sifan Wang
Ananyae Kumar Bhartari
Bowen Li
P. Perdikaris
PINN
54
4
0
02 Feb 2025
Transfer Learning in Physics-Informed Neural Networks: Full Fine-Tuning, Lightweight Fine-Tuning, and Low-Rank Adaptation
Transfer Learning in Physics-Informed Neural Networks: Full Fine-Tuning, Lightweight Fine-Tuning, and Low-Rank Adaptation
Yizheng Wang
Jinshuai Bai
M. Eshaghi
C. Anitescu
X. Zhuang
Timon Rabczuk
Yinghua Liu
AI4CE
46
1
0
02 Feb 2025
STAF: Sinusoidal Trainable Activation Functions for Implicit Neural Representation
STAF: Sinusoidal Trainable Activation Functions for Implicit Neural Representation
Alireza Morsali
MohammadJavad Vaez
Hossein Soltani
A. Kazerouni
Babak Taati
Morteza Mohammad-Noori
115
1
0
02 Feb 2025
On the study of frequency control and spectral bias in Wavelet-Based Kolmogorov Arnold networks: A path to physics-informed KANs
On the study of frequency control and spectral bias in Wavelet-Based Kolmogorov Arnold networks: A path to physics-informed KANs
Juan Daniel Meshir
Abel Palafox
Edgar Alejandro Guerrero
57
3
0
01 Feb 2025
Sub-Sequential Physics-Informed Learning with State Space Model
Sub-Sequential Physics-Informed Learning with State Space Model
Chenhui Xu
Dancheng Liu
Yuting Hu
Jiajie Li
Ruiyang Qin
Qingxiao Zheng
Jinjun Xiong
AI4CE
PINN
129
0
0
01 Feb 2025
MILP initialization for solving parabolic PDEs with PINNs
Sirui Li
Federica Bragone
Matthieu Barreau
Kateryna Morozovska
33
0
0
28 Jan 2025
An explainable operator approximation framework under the guideline of
  Green's function
An explainable operator approximation framework under the guideline of Green's function
Jianghang Gu
Ling Wen
Yuntian Chen
Shiyi Chen
64
0
0
21 Dec 2024
A physics-informed transformer neural operator for learning generalized solutions of initial boundary value problems
A physics-informed transformer neural operator for learning generalized solutions of initial boundary value problems
Sumanth Kumar Boya
Deepak Subramani
AI4CE
94
0
0
12 Dec 2024
Is the neural tangent kernel of PINNs deep learning general partial
  differential equations always convergent ?
Is the neural tangent kernel of PINNs deep learning general partial differential equations always convergent ?
Zijian Zhou
Zhenya Yan
92
10
0
09 Dec 2024
Advancing Generalization in PINNs through Latent-Space Representations
Advancing Generalization in PINNs through Latent-Space Representations
Honghui Wang
Yifan Pu
Shiji Song
Gao Huang
AI4CE
PINN
64
0
0
28 Nov 2024
A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural
  Network Training on Solving Partial Differential Equations
A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural Network Training on Solving Partial Differential Equations
Shu Liu
Stanley Osher
Wuchen Li
28
0
0
09 Nov 2024
Theoretical characterisation of the Gauss-Newton conditioning in Neural Networks
Theoretical characterisation of the Gauss-Newton conditioning in Neural Networks
Jim Zhao
Sidak Pal Singh
Aurélien Lucchi
AI4CE
39
0
0
04 Nov 2024
Projected Neural Differential Equations for Learning Constrained
  Dynamics
Projected Neural Differential Equations for Learning Constrained Dynamics
Alistair J R White
Anna Buttner
Maximilian Gelbrecht
Valentin Duruisseaux
Niki Kilbertus
Frank Hellmann
Niklas Boers
39
0
0
31 Oct 2024
PINNing Cerebral Blood Flow: Analysis of Perfusion MRI in Infants using
  Physics-Informed Neural Networks
PINNing Cerebral Blood Flow: Analysis of Perfusion MRI in Infants using Physics-Informed Neural Networks
C. Galazis
Ching-En Chiu
Tomoki Arichi
Anil A. Bharath
Marta Varela
27
0
0
11 Oct 2024
Enhanced physics-informed neural networks (PINNs) for high-order power
  grid dynamics
Enhanced physics-informed neural networks (PINNs) for high-order power grid dynamics
Vineet Jagadeesan Nair
PINN
38
0
0
10 Oct 2024
Learning a Neural Solver for Parametric PDE to Enhance Physics-Informed
  Methods
Learning a Neural Solver for Parametric PDE to Enhance Physics-Informed Methods
Lise Le Boudec
Emmanuel de Bezenac
Louis Serrano
Ramon Daniel Regueiro-Espino
Yuan Yin
Patrick Gallinari
AI4CE
30
2
0
09 Oct 2024
Quantifying Training Difficulty and Accelerating Convergence in Neural
  Network-Based PDE Solvers
Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers
Chuqi Chen
Qixuan Zhou
Yahong Yang
Yang Xiang
Tao Luo
29
1
0
08 Oct 2024
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
16
0
0
08 Oct 2024
DimOL: Dimensional Awareness as A New 'Dimension' in Operator Learning
DimOL: Dimensional Awareness as A New 'Dimension' in Operator Learning
Yichen Song
Yunbo Wang
Xiaokang Yang
Xiaokang Yang
AI4CE
53
0
0
08 Oct 2024
Sinc Kolmogorov-Arnold Network and Its Applications on Physics-informed
  Neural Networks
Sinc Kolmogorov-Arnold Network and Its Applications on Physics-informed Neural Networks
Tianchi Yu
Jingwei Qiu
Jiang Yang
Ivan V. Oseledets
21
2
0
05 Oct 2024
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