Characterizing possible failure modes in physics-informed neural networks

2 September 2021

Aditi S. Krishnapriyan

Papers citing "Characterizing possible failure modes in physics-informed neural networks"

25 / 325 papers shown

Title
On the Role of Fixed Points of Dynamical Systems in Training Physics-Informed Neural Networks Franz M. Rohrhofer S. Posch C. Gößnitzer Bernhard C. Geiger PINN 36 17 0 25 Mar 2022
Investigating Compounding Prediction Errors in Learned Dynamics Models Nathan Lambert K. Pister Roberto Calandra AI4CE 16 27 0 17 Mar 2022
Respecting causality is all you need for training physics-informed neural networks Sizhuang He Shyam Sankaran P. Perdikaris PINN CML AI4CE 46 199 0 14 Mar 2022
Modeling the Shape of the Brain Connectome via Deep Neural Networks Haocheng Dai M. Bauer P. T. Fletcher S. Joshi MedIm DiffM 17 1 0 06 Mar 2022
AutoIP: A United Framework to Integrate Physics into Gaussian Processes D. Long Zhilin Wang Aditi S. Krishnapriyan Robert M. Kirby Shandian Zhe Michael W. Mahoney AI4CE 29 14 0 24 Feb 2022
Learning Physics-Informed Neural Networks without Stacked Back-propagation Di He Shanda Li Wen-Wu Shi Xiaotian Gao Jia Zhang Jiang Bian Liwei Wang Tie-Yan Liu DiffM PINN AI4CE 18 23 0 18 Feb 2022
Learning continuous models for continuous physics Aditi S. Krishnapriyan A. Queiruga N. Benjamin Erichson Michael W. Mahoney AI4CE 26 33 0 17 Feb 2022
When Do Flat Minima Optimizers Work? Jean Kaddour Linqing Liu Ricardo M. A. Silva Matt J. Kusner ODL 24 58 0 01 Feb 2022
Numerical Approximation of Partial Differential Equations by a Variable Projection Method with Artificial Neural Networks S. Dong Jielin Yang 40 17 0 24 Jan 2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next S. Cuomo Vincenzo Schiano Di Cola F. Giampaolo G. Rozza Maizar Raissi F. Piccialli PINN 26 1,180 0 14 Jan 2022
Learning finite difference methods for reaction-diffusion type equations with FCNN Yongho Kim Yongho Choi 13 8 0 04 Jan 2022
Learning from learning machines: a new generation of AI technology to meet the needs of science L. Pion-Tonachini K. Bouchard Héctor García Martín S. Peisert W. B. Holtz ... Rick L. Stevens Mark Anderson Ken Kreutz-Delgado Michael W. Mahoney James B. Brown 32 7 0 27 Nov 2021
On Computing the Hyperparameter of Extreme Learning Machines: Algorithm and Application to Computational PDEs, and Comparison with Classical and High-Order Finite Elements S. Dong Jielin Yang 72 52 0 27 Oct 2021
Fast PDE-constrained optimization via self-supervised operator learning Sizhuang He Mohamed Aziz Bhouri P. Perdikaris 47 28 0 25 Oct 2021
NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs Biswajit Khara Aditya Balu Ameya Joshi S. Sarkar C. Hegde A. Krishnamurthy Baskar Ganapathysubramanian 26 19 0 04 Oct 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 39 65 0 02 Jul 2021
Learning Green's Functions of Linear Reaction-Diffusion Equations with Application to Fast Numerical Solver Yuankai Teng Xiaoping Zhang Zhu Wang L. Ju 16 14 0 23 May 2021
Data vs. Physics: The Apparent Pareto Front of Physics-Informed Neural Networks Franz M. Rohrhofer S. Posch C. Gößnitzer Bernhard C. Geiger PINN 23 39 0 03 May 2021
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 41 494 0 09 Feb 2021
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
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sizhuang He Hanwen Wang P. Perdikaris 131 438 0 18 Dec 2020
$NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework$ NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework O. Hennigh S. Narasimhan M. A. Nabian Akshay Subramaniam Kaustubh Tangsali M. Rietmann J. Ferrandis Wonmin Byeon Z. Fang S. Choudhry PINN AI4CE 93 126 0 14 Dec 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 91 387 0 10 Mar 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 139 424 0 10 Mar 2020
Hamiltonian neural networks for solving equations of motion M. Mattheakis David Sondak Akshunna S. Dogra P. Protopapas 27 56 0 29 Jan 2020