Respecting causality is all you need for training physics-informed neural networks

14 March 2022

Papers citing "Respecting causality is all you need for training physics-informed neural networks"

50 / 122 papers shown

Title
Learning and Transferring Physical Models through Derivatives Alessandro Trenta Andrea Cossu Davide Bacciu AI4CE 36 0 0 02 May 2025
Gradient Alignment in Physics-informed Neural Networks: A Second-Order Optimization Perspective Sifan Wang Ananyae Kumar Bhartari Bowen Li P. Perdikaris PINN 56 4 0 02 Feb 2025
Variational autoencoders with latent high-dimensional steady geometric flows for dynamics Andrew Gracyk DRL 69 0 0 03 Jan 2025
About rectified sigmoid function for enhancing the accuracy of Physics-Informed Neural Networks V. A. Es'kin Alexey O. Malkhanov Mikhail E. Smorkalov MLT 41 0 0 31 Dec 2024
Advancing Generalization in PINNs through Latent-Space Representations Honghui Wang Yifan Pu Shiji Song Gao Huang AI4CE PINN 69 0 0 28 Nov 2024
Coupled Integral PINN for conservation law Yeping Wang Shihao Yang PINN 24 0 0 18 Nov 2024
SPIKANs: Separable Physics-Informed Kolmogorov-Arnold Networks Bruno Jacob Amanda A. Howard P. Stinis 37 6 0 09 Nov 2024
LE-PDE++: Mamba for accelerating PDEs Simulations Aoming Liang Zhaoyang Mu Qi liu Ruipeng Li Mingming Ge Dixia Fan AI4CE 39 0 0 04 Nov 2024
TRADE: Transfer of Distributions between External Conditions with Normalizing Flows Stefan Wahl Armand Rousselot Felix Dräxler Ullrich Kothe Ullrich Köthe 26 0 0 25 Oct 2024
HyResPINNs: Hybrid Residual Networks for Adaptive Neural and RBF Integration in Solving PDEs Madison Cooley Robert M. Kirby Shandian Zhe Varun Shankar PINN AI4CE 28 0 0 04 Oct 2024
Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases Madison Cooley Varun Shankar Robert M. Kirby Shandian Zhe 24 2 0 04 Oct 2024
Dual Cone Gradient Descent for Training Physics-Informed Neural Networks Youngsik Hwang Dong-Young Lim AI4CE 30 2 0 27 Sep 2024
Non-overlapping, Schwarz-type Domain Decomposition Method for Physics and Equality Constrained Artificial Neural Networks Qifeng Hu S. Basir Inanc Senocak 35 0 0 20 Sep 2024
ASPINN: An asymptotic strategy for solving singularly perturbed differential equations Sen Wang Peizhi Zhao Tao Song 30 0 0 20 Sep 2024
Physics-Informed Neural Networks with Trust-Region Sequential Quadratic Programming Xiaoran Cheng Sen Na PINN 37 1 0 16 Sep 2024
Fourier Spectral Physics Informed Neural Network: An Efficient and Low-Memory PINN Tianchi Yu Yiming Qi Ivan V. Oseledets Shiyi Chen 24 1 0 29 Aug 2024
Domain-decoupled Physics-informed Neural Networks with Closed-form Gradients for Fast Model Learning of Dynamical Systems Henrik Krauss Tim-Lukas Habich Max Bartholdt Thomas Seel Moritz Schappler PINN AI4CE 40 2 0 27 Aug 2024
Functional Tensor Decompositions for Physics-Informed Neural Networks Sai Karthikeya Vemuri Tim Buchner Julia Niebling Joachim Denzler PINN 38 4 0 23 Aug 2024
Physics Informed Deep Learning for Strain Gradient Continuum Plasticity Ankit Tyagi Uttam Suman Mariya Mamajiwala Debasish Roy PINN AI4CE 24 1 0 13 Aug 2024
Finite basis Kolmogorov-Arnold networks: domain decomposition for data-driven and physics-informed problems Amanda A. Howard Bruno Jacob Sarah H. Murphy Alexander Heinlein P. Stinis AI4CE 36 26 0 28 Jun 2024
Adapting Physics-Informed Neural Networks to Improve ODE Optimization in Mosquito Population Dynamics D. V. Cuong Branislava Lalić Mina Petrić Binh Nguyen M. Roantree PINN AI4CE 47 2 0 07 Jun 2024
Astral: training physics-informed neural networks with error majorants V. Fanaskov Tianchi Yu Alexander Rudikov Ivan V. Oseledets 33 1 0 04 Jun 2024
Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks Felix Dangel Johannes Müller Marius Zeinhofer ODL 26 6 0 24 May 2024
Gradient Flow Based Phase-Field Modeling Using Separable Neural Networks R. Mattey Susanta Ghosh AI4CE 43 1 0 09 May 2024
Geometry-aware framework for deep energy method: an application to structural mechanics with hyperelastic materials Thi Nguyen Khoa Nguyen T. Dairay Raphael Meunier Christophe Millet Mathilde Mougeot AI4CE PINN 43 0 0 06 May 2024
Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations Nima Hosseini Dashtbayaz G. Farhani Boyu Wang Charles X. Ling 26 1 0 02 May 2024
KAN: Kolmogorov-Arnold Networks Ziming Liu Yixuan Wang Sachin Vaidya Fabian Ruehle James Halverson Marin Soljacic Thomas Y. Hou Max Tegmark 83 473 0 30 Apr 2024
Optimal time sampling in physics-informed neural networks Gabriel Turinici PINN 24 1 0 29 Apr 2024
PINNACLE: PINN Adaptive ColLocation and Experimental points selection Gregory Kang Ruey Lau Apivich Hemachandra See-Kiong Ng K. H. Low 3DPC 31 18 0 11 Apr 2024
Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes Ming Zhong Dehao Liu Raymundo Arroyave U. Braga-Neto AI4CE SSL 26 1 0 08 Apr 2024
Fully-fused Multi-Layer Perceptrons on Intel Data Center GPUs Kai Yuan Christoph Bauinger Xiangyi Zhang Pascal Baehr Matthias Kirchhart Darius Dabert Adrien Tousnakhoff Pierre Boudier Michael Paulitsch 34 2 0 26 Mar 2024
Learning Traveling Solitary Waves Using Separable Gaussian Neural Networks Siyuan Xing E. Charalampidis 23 0 0 07 Mar 2024
Causal hybrid modeling with double machine learning Kai-Hendrik Cohrs Gherardo Varando Nuno Carvalhais Markus Reichstein Gustau Camps-Valls 21 4 0 20 Feb 2024
Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust Metrics Michael Penwarden H. Owhadi Robert M. Kirby AI4CE 22 1 0 16 Feb 2024
Feature Mapping in Physics-Informed Neural Networks (PINNs) Chengxi Zeng T. Burghardt A. Gambaruto 41 1 0 10 Feb 2024
Densely Multiplied Physics Informed Neural Networks Feilong Jiang Xiaonan Hou Min Xia PINN 19 2 0 06 Feb 2024
Challenges in Training PINNs: A Loss Landscape Perspective Pratik Rathore Weimu Lei Zachary Frangella Lu Lu Madeleine Udell AI4CE PINN ODL 35 39 0 02 Feb 2024
Preconditioning for Physics-Informed Neural Networks Songming Liu Chang Su J. Yao Zhongkai Hao Hang Su Youjia Wu Jun Zhu AI4CE PINN 36 5 0 01 Feb 2024
PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks Sifan Wang Bowen Li Yuhan Chen P. Perdikaris AI4CE PINN 26 27 0 01 Feb 2024
Closure Discovery for Coarse-Grained Partial Differential Equations Using Grid-based Reinforcement Learning Jan-Philipp von Bassewitz Sebastian Kaltenbach P. Koumoutsakos AI4CE 35 2 0 01 Feb 2024
Separable Physics-Informed Neural Networks for the solution of elasticity problems V. A. Es'kin Danil V. Davydov Julia V. Guréva Alexey O. Malkhanov Mikhail E. Smorkalov PINN AI4CE 25 2 0 24 Jan 2024
Approximation of Solution Operators for High-dimensional PDEs Nathan Gaby Xiaojing Ye 27 0 0 18 Jan 2024
Efficient Discrete Physics-informed Neural Networks for Addressing Evolutionary Partial Differential Equations Siqi Chen Bin Shan Ye Li AI4CE PINN 23 1 0 22 Dec 2023
Physics-informed Neural Network Estimation of Material Properties in Soft Tissue Nonlinear Biomechanical Models Federica Caforio Francesco Regazzoni S. Pagani Elias Karabelas Christoph M. Augustin Gundolf Haase Gernot Plank A. Quarteroni PINN 16 12 0 15 Dec 2023
Exactly conservative physics-informed neural networks and deep operator networks for dynamical systems E. Cardoso-Bihlo Alex Bihlo AI4CE PINN 42 4 0 23 Nov 2023
Stacked networks improve physics-informed training: applications to neural networks and deep operator networks Amanda A. Howard Sarah H. Murphy Shady E. Ahmed P. Stinis AI4CE 50 18 0 11 Nov 2023
Solving High Frequency and Multi-Scale PDEs with Gaussian Processes Shikai Fang Madison Cooley Da Long Shibo Li R. Kirby Shandian Zhe 35 4 0 08 Nov 2023
Transfer learning for improved generalizability in causal physics-informed neural networks for beam simulations Taniya Kapoor Hongrui Wang Alfredo Núñez R. Dollevoet AI4CE PINN 19 15 0 01 Nov 2023
TSONN: Time-stepping-oriented neural network for solving partial differential equations W. Cao Weiwei Zhang AI4TS 16 1 0 25 Oct 2023
Adversarial Training for Physics-Informed Neural Networks Yao Li Shengzhu Shi Zhichang Guo Boying Wu AAML PINN 25 0 0 18 Oct 2023