Physics-informed neural networks (PINNs) for fluid mechanics: A review

20 May 2021

Papers citing "Physics-informed neural networks (PINNs) for fluid mechanics: A review"

39 / 39 papers shown

Title
QCPINN: Quantum-Classical Physics-Informed Neural Networks for Solving PDEs Afrah Farea Saiful Khan Mustafa Serdar Celebi PINN 101 0 0 20 Mar 2025
Towards a Foundation Model for Physics-Informed Neural Networks: Multi-PDE Learning with Active Sampling Keon Vin Park PINN AI4CE 78 0 0 11 Feb 2025
Multi-Parameter Molecular MRI Quantification using Physics-Informed Self-Supervised Learning Alex Finkelstein Nikita Vladimirov Moritz Zaiss O. Perlman 53 2 0 10 Nov 2024
Metamizer: a versatile neural optimizer for fast and accurate physics simulations Nils Wandel Stefan Schulz Reinhard Klein PINN AI4CE 75 1 0 10 Oct 2024
Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases Madison Cooley Varun Shankar Robert M. Kirby Shandian Zhe 68 2 0 04 Oct 2024
SetPINNs: Set-based Physics-informed Neural Networks Mayank Nagda Phil Ostheimer Thomas Specht Frank Rhein Fabian Jirasek Stephan Mandt Marius Kloft Sophie Fellenz PINN 3DPC 113 1 0 30 Sep 2024
Scientific Machine Learning Seismology Tomohisa Okazaki PINN AI4CE 103 0 0 27 Sep 2024
Generating Physical Dynamics under Priors Zihan Zhou Xiaoxue Wang Tianshu Yu DiffM AI4CE 89 0 0 01 Sep 2024
A Two-Stage Imaging Framework Combining CNN and Physics-Informed Neural Networks for Full-Inverse Tomography: A Case Study in Electrical Impedance Tomography (EIT) Xu Yang Yangming Zhang Haofeng Chen Gang Ma Xiaojie Wang 49 0 0 25 Jul 2024
Regression Trees Know Calculus Nathan Wycoff 47 0 0 22 May 2024
Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling Wanghan Xu Fenghua Ling Wenlong Zhang Tao Han Hao Chen Wanli Ouyang Lei Bai AI4CE 114 5 0 22 May 2024
Stochastic Inference of Plate Bending from Heterogeneous Data: Physics-informed Gaussian Processes via Kirchhoff-Love Theory I. Kavrakov Gledson Rodrigo Tondo Guido Morgenthal AI4CE 81 1 0 21 May 2024
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 138 280 0 20 Apr 2021
Physics-aware deep neural networks for surrogate modeling of turbulent natural convection Didier Lucor A. Agrawal A. Sergent PINN AI4CE 31 16 0 05 Mar 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 76 508 0 09 Feb 2021
$NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework$ 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 110 127 0 14 Dec 2020
Physics-Informed Neural Networks for Nonhomogeneous Material Identification in Elasticity Imaging Enrui Zhang Minglang Yin George Karniadakis 30 64 0 02 Sep 2020
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 111 896 0 28 Jul 2020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating a class of inverse problems for PDEs Siddhartha Mishra Roberto Molinaro PINN 35 263 0 29 Jun 2020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs Siddhartha Mishra Roberto Molinaro PINN 45 172 0 29 Jun 2020
Deep learning of free boundary and Stefan problems Sizhuang He P. Perdikaris 102 81 0 04 Jun 2020
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 213 768 0 13 Mar 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 158 520 0 11 Mar 2020
Understanding and mitigating gradient pathologies in physics-informed neural networks Sizhuang He Yujun Teng P. Perdikaris AI4CE PINN 85 292 0 13 Jan 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 302 42,038 0 03 Dec 2019
Towards Physics-informed Deep Learning for Turbulent Flow Prediction Rui Wang K. Kashinath M. Mustafa A. Albert Rose Yu PINN AI4CE 36 361 0 20 Nov 2019
$Transfer learning enhanced physics informed neural network for phase-field modeling of fracture$ Transfer learning enhanced physics informed neural network for phase-field modeling of fracture S. Goswami C. Anitescu S. Chakraborty Timon Rabczuk PINN 42 602 0 04 Jul 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 107 368 0 13 May 2019
Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks Dongkun Zhang Ling Guo George Karniadakis AI4CE 58 212 0 03 May 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data Yinhao Zhu N. Zabaras P. Koutsourelakis P. Perdikaris PINN AI4CE 70 860 0 18 Jan 2019
Adversarial Uncertainty Quantification in Physics-Informed Neural Networks Yibo Yang P. Perdikaris AI4CE PINN 89 356 0 09 Nov 2018
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems Dongkun Zhang Lu Lu Ling Guo George Karniadakis UQCV 100 405 0 21 Sep 2018
Deep Learning of Vortex Induced Vibrations M. Raissi Zhicheng Wang M. Triantafyllou George Karniadakis AI4CE 43 373 0 26 Aug 2018
Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations M. Raissi P. Perdikaris George Karniadakis PINN AI4CE 54 611 0 28 Nov 2017
Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations M. Raissi P. Perdikaris George Karniadakis PINN AI4CE 68 912 0 28 Nov 2017
Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations M. Raissi P. Perdikaris George Karniadakis 53 267 0 29 Mar 2017
Machine Learning of Linear Differential Equations using Gaussian Processes M. Raissi George Karniadakis 64 544 0 10 Jan 2017
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Zhiwen Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 356 18,300 0 27 May 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.1K 149,474 0 22 Dec 2014