Understanding and mitigating gradient pathologies in physics-informed neural networks

13 January 2020

Papers citing "Understanding and mitigating gradient pathologies in physics-informed neural networks"

50 / 114 papers shown

Title
Surrogate-data-enriched Physics-Aware Neural Networks Raphael Leiteritz Patrick Buchfink B. Haasdonk Dirk Pflüger PINN AI4CE 22 3 0 10 Dec 2021
A generic physics-informed neural network-based framework for reliability assessment of multi-state systems Taotao Zhou Xiaoge Zhang E. Droguett A. Mosleh AI4CE 20 31 0 01 Dec 2021
Physics-enhanced Neural Networks in the Small Data Regime Jonas Eichelsdörfer Sebastian Kaltenbach P. Koutsourelakis AI4CE PINN 16 5 0 19 Nov 2021
Learning To Estimate Regions Of Attraction Of Autonomous Dynamical Systems Using Physics-Informed Neural Networks Cody Scharzenberger Joe Hays 40 3 0 18 Nov 2021
Learning Free-Surface Flow with Physics-Informed Neural Networks Raphael Leiteritz Marcel Hurler Dirk Pflüger PINN AI4CE 30 7 0 17 Nov 2021
Parallel Physics-Informed Neural Networks with Bidirectional Balance Yuhao Huang PINN AI4CE 14 2 0 10 Nov 2021
Constructing Neural Network-Based Models for Simulating Dynamical Systems Christian Møldrup Legaard Thomas Schranz G. Schweiger Ján Drgovna Basak Falay C. Gomes Alexandros Iosifidis M. Abkar P. Larsen PINN AI4CE 33 93 0 02 Nov 2021
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems Jeremy Yu Lu Lu Xuhui Meng George Karniadakis PINN AI4CE 38 451 0 01 Nov 2021
CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method P. Chiu Jian Cheng Wong C. Ooi M. Dao Yew-Soon Ong PINN 31 207 0 29 Oct 2021
Polynomial-Spline Neural Networks with Exact Integrals Jonas A. Actor Andrew Huang N. Trask 23 1 0 26 Oct 2021
Multi-Objective Loss Balancing for Physics-Informed Deep Learning Rafael Bischof M. Kraus PINN AI4CE 33 92 0 19 Oct 2021
Physics informed neural networks for continuum micromechanics Alexander Henkes Henning Wessels R. Mahnken PINN AI4CE 16 139 0 14 Oct 2021
A Review of Physics-based Machine Learning in Civil Engineering S. Vadyala S. N. Betgeri J. Matthews Elizabeth Matthews AI4CE 25 152 0 09 Oct 2021
Study of Drug Assimilation in Human System using Physics Informed Neural Networks Kanupriya Goswami Arpana Sharma Madhu Pruthi Richa Gupta 14 10 0 08 Oct 2021
Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training E. Haghighat Daniel Amini R. Juanes PINN AI4CE 23 95 0 06 Oct 2021
On the Correspondence between Gaussian Processes and Geometric Harmonics Felix Dietrich J. M. Bello-Rivas Ioannis G. Kevrekidis 21 3 0 05 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
Differentiable Spline Approximations Minsu Cho Aditya Balu Ameya Joshi Anjana Prasad Biswajit Khara S. Sarkar Baskar Ganapathysubramanian A. Krishnamurthy C. Hegde 30 4 0 04 Oct 2021
Learning in Sinusoidal Spaces with Physics-Informed Neural Networks Jian Cheng Wong C. Ooi Abhishek Gupta Yew-Soon Ong AI4CE PINN SSL 18 76 0 20 Sep 2021
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed Hermite-Spline CNNs Nils Wandel Michael Weinmann Michael Neidlin Reinhard Klein AI4CE 58 60 0 15 Sep 2021
Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling Kookjin Lee Nathaniel Trask P. Stinis 35 25 0 11 Sep 2021
DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks Christian Moya Guang Lin AI4CE PINN 62 37 0 09 Sep 2021
AdjointNet: Constraining machine learning models with physics-based codes S. Karra B. Ahmmed M. Mudunuru AI4CE PINN OOD 18 4 0 08 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 51 610 0 02 Sep 2021
SURFNet: Super-resolution of Turbulent Flows with Transfer Learning using Small Datasets Octavi Obiols-Sales Abhinav Vishnu Nicholas Malaya Aparna Chandramowlishwaran AI4CE 34 24 0 17 Aug 2021
Reconstructing a dynamical system and forecasting time series by self-consistent deep learning Zhe Wang C. Guet AI4TS 16 4 0 04 Aug 2021
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 48 210 0 16 Jul 2021
Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks S. Maddu D. Sturm Christian L. Müller I. Sbalzarini AI4CE 29 81 0 02 Jul 2021
Transient Stability Analysis with Physics-Informed Neural Networks Jochen Stiasny Georgios S. Misyris Spyros Chatzivasileiadis PINN 23 13 0 25 Jun 2021
Long-time integration of parametric evolution equations with physics-informed DeepONets Sizhuang He P. Perdikaris AI4CE 24 117 0 09 Jun 2021
Encoding physics to learn reaction-diffusion processes Chengping Rao Pu Ren Qi Wang O. Buyukozturk Haoqin Sun Yang Liu PINN AI4CE DiffM 33 78 0 09 Jun 2021
PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics Arka Daw M. Maruf Anuj Karpatne AI4CE 10 41 0 06 Jun 2021
Choose a Transformer: Fourier or Galerkin Shuhao Cao 42 225 0 31 May 2021
Optimal Transport Based Refinement of Physics-Informed Neural Networks Vaishnav Tadiparthi R. Bhattacharya OT 15 2 0 26 May 2021
Physics-informed neural networks (PINNs) for fluid mechanics: A review Shengze Cai Zhiping Mao Zhicheng Wang Minglang Yin George Karniadakis PINN AI4CE 25 1,128 0 20 May 2021
Deep learning in physics: a study of dielectric quasi-cubic particles in a uniform electric field Zhe Wang C. Guet 14 5 0 11 May 2021
Hard Encoding of Physics for Learning Spatiotemporal Dynamics Chengping Rao Hao Sun Yang Liu PINN AI4CE 29 11 0 02 May 2021
Mosaic Flows: A Transferable Deep Learning Framework for Solving PDEs on Unseen Domains Hengjie Wang R. Planas Aparna Chandramowlishwaran Ramin Bostanabad AI4CE 50 61 0 22 Apr 2021
Exact imposition of boundary conditions with distance functions in physics-informed deep neural networks N. Sukumar Ankit Srivastava PINN AI4CE 41 241 0 17 Apr 2021
Physics-informed neural networks for the shallow-water equations on the sphere Alexander Bihlo R. Popovych 14 77 0 01 Apr 2021
Stiff Neural Ordinary Differential Equations Suyong Kim Weiqi Ji Sili Deng Yingbo Ma Chris Rackauckas AI4CE 19 143 0 29 Mar 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 59 653 0 20 Mar 2021
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets Sizhuang He Hanwen Wang P. Perdikaris AI4CE 40 667 0 19 Mar 2021
Evolutional Deep Neural Network Yifan Du T. Zaki 29 68 0 18 Mar 2021
The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers? Stefano Markidis PINN 39 182 0 12 Mar 2021
Physics-aware deep neural networks for surrogate modeling of turbulent natural convection Didier Lucor A. Agrawal A. Sergent PINN AI4CE 17 16 0 05 Mar 2021
Partition of unity networks: deep hp-approximation Kookjin Lee N. Trask Ravi G. Patel Mamikon A. Gulian E. Cyr 22 30 0 27 Jan 2021
Hybrid FEM-NN models: Combining artificial neural networks with the finite element method Sebastian K. Mitusch S. Funke M. Kuchta AI4CE 31 93 0 04 Jan 2021
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 131 439 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