Investigating and Mitigating Failure Modes in Physics-informed Neural
Networks (PINNs)

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Investigating and Mitigating Failure Modes in Physics-informed Neural Networks (PINNs)

20 September 2022

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Papers citing "Investigating and Mitigating Failure Modes in Physics-informed Neural Networks (PINNs)"

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Title
Critical Investigation of Failure Modes in Physics-informed Neural Networks S. Basir Inanc Senocak PINN AI4CE 62 21 0 20 Jun 2022
Physics and Equality Constrained Artificial Neural Networks: Application to Forward and Inverse Problems with Multi-fidelity Data Fusion S. Basir Inanc Senocak PINN AI4CE 79 70 0 30 Sep 2021
Characterizing possible failure modes in physics-informed neural networks Aditi S. Krishnapriyan A. Gholami Shandian Zhe Robert M. Kirby Michael W. Mahoney PINN AI4CE 116 647 0 02 Sep 2021
$Physics-informed neural networks for solving Reynolds-averaged Navier$\unicode{x2013}$Stokes equations$ Physics-informed neural networks for solving Reynolds-averaged Navier $\unicode{x2013}$ Stokes equations Hamidreza Eivazi M. Tahani P. Schlatter Ricardo Vinuesa PINN AI4CE 59 265 0 22 Jul 2021
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism L. McClenny U. Braga-Neto PINN 80 459 0 07 Sep 2020
A Dual-Dimer Method for Training Physics-Constrained Neural Networks with Minimax Architecture Dehao Liu Yan Wang 123 75 0 01 May 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 520 42,449 0 03 Dec 2019
Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks Georgios Kissas Yibo Yang E. Hwuang W. Witschey John A. Detre P. Perdikaris AI4CE 123 373 0 13 May 2019
Deep Learning of Vortex Induced Vibrations M. Raissi Zhicheng Wang M. Triantafyllou George Karniadakis AI4CE 60 376 0 26 Aug 2018
Visualizing the Loss Landscape of Neural Nets Hao Li Zheng Xu Gavin Taylor Christoph Studer Tom Goldstein 252 1,893 0 28 Dec 2017
The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems E. Weinan Ting Yu 121 1,387 0 30 Sep 2017
DGM: A deep learning algorithm for solving partial differential equations Justin A. Sirignano K. Spiliopoulos AI4CE 91 2,063 0 24 Aug 2017
An overview of gradient descent optimization algorithms Sebastian Ruder ODL 204 6,199 0 15 Sep 2016
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 326 18,625 0 06 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,260 0 22 Dec 2014