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

28 July 2020

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 Sidharth S. Menon Ameya D. Jagtap PINN 107 0 0 06 May 2025
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
Integration Matters for Learning PDEs with Backwards SDEs Sungje Park Stephen Tu PINN 50 0 0 02 May 2025
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
Multi-level datasets training method in Physics-Informed Neural Networks Yao-Hsuan Tsai Hsiao-Tung Juan Pao-Hsiung Chiu Chao-An Lin AI4CE 39 0 0 30 Apr 2025
Reliable and Efficient Inverse Analysis using Physics-Informed Neural Networks with Distance Functions and Adaptive Weight Tuning Shota Deguchi Mitsuteru Asai PINN AI4CE 78 0 0 25 Apr 2025
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 Samuel Audia S. Feizi Matthias Zwicker Dinesh Manocha 23 0 0 18 Apr 2025
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 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 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 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 Marius Almanstötter Roman Vetter Dagmar Iber PINN 32 1 0 07 Apr 2025
Hard-constraining Neumann boundary conditions in physics-informed neural networks via Fourier feature embeddings Christopher Straub Philipp Brendel Vlad Medvedev A. Rosskopf 38 0 0 01 Apr 2025
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
Integral regularization PINNs for evolution equations Xiaodong Feng Haojiong Shangguan Tao Tang Xiaoliang Wan PINN 57 0 0 31 Mar 2025
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
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 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 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
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
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
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 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 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
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
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 48 1 0 02 Feb 2025
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
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 132 0 0 01 Feb 2025
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 59 3 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 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 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 ? Zijian Zhou Zhenya Yan 92 10 0 09 Dec 2024
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 Shu Liu Stanley Osher Wuchen Li 28 0 0 09 Nov 2024
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 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 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 Vineet Jagadeesan Nair PINN 38 0 0 10 Oct 2024
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 Chuqi Chen Qixuan Zhou Yahong Yang Yang Xiang Tao Luo 29 1 0 08 Oct 2024
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 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 Tianchi Yu Jingwei Qiu Jiang Yang Ivan V. Oseledets 21 2 0 05 Oct 2024