The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers?

12 March 2021

Papers citing "The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers?"

49 / 49 papers shown

Title
Deterministic Global Optimization of the Acquisition Function in Bayesian Optimization: To Do or Not To Do? Anastasia S. Georgiou Daniel Jungen Luise F. Kaven Verena Hunstig Constantine Frangakis Ioannis G. Kevrekidis Alexander Mitsos 33 0 0 05 Mar 2025
REAct: Rational Exponential Activation for Better Learning and Generalization in PINNs Sourav Mishra Shreya Hallikeri Suresh Sundaram AI4CE 34 0 0 04 Mar 2025
Learning Discontinuous Galerkin Solutions to Elliptic Problems via Small Linear Convolutional Neural Networks A. Celaya Yimo Wang David T. Fuentes Beatrice Riviere 38 0 0 12 Feb 2025
Integrating Physics-Informed Deep Learning and Numerical Methods for Robust Dynamics Discovery and Parameter Estimation Caitlin Ho Andrea Arnold AI4CE PINN 26 0 0 05 Oct 2024
Component Fourier Neural Operator for Singularly Perturbed Differential Equations Ye Li Ting Du Yiwen Pang Zhongyi Huang 16 1 0 07 Sep 2024
Adapting Physics-Informed Neural Networks for Bifurcation Detection in Ecological Migration Models Lujie Yin Xing Lv PINN 15 0 0 01 Sep 2024
General-Kindred Physics-Informed Neural Network to the Solutions of Singularly Perturbed Differential Equations Sen Wang Peizhi Zhao Qinglong Ma Tao Song PINN 18 3 0 27 Aug 2024
Physics-Informed Neural Networks for Dynamic Process Operations with Limited Physical Knowledge and Data M. Velioglu Song Zhai Sophia Rupprecht Alexander Mitsos Andreas Jupke Manuel Dahmen PINN AI4CE 44 4 0 03 Jun 2024
Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks Felix Dangel Johannes Müller Marius Zeinhofer ODL 21 6 0 24 May 2024
Physics-Informed Machine Learning On Polar Ice: A Survey Zesheng Liu Younghyun Koo Maryam Rahnemoonfar PINN AI4CE 29 1 0 30 Apr 2024
Toward a Better Understanding of Fourier Neural Operators: Analysis and Improvement from a Spectral Perspective Shaoxiang Qin Fuyuan Lyu Wenhui Peng Dingyang Geng Ju Wang Naiping Gao Xue Liu L. Wang AI4CE 24 3 0 10 Apr 2024
Data assimilation and parameter identification for water waves using the nonlinear Schrödinger equation and physics-informed neural networks Svenja Ehlers Niklas A. Wagner Annamaria Scherzl Marco Klein Norbert Hoffmann M. Stender 11 1 0 08 Jan 2024
Data-Driven Physics-Informed Neural Networks: A Digital Twin Perspective Sunwoong Yang Hojin Kim Y. Hong K. Yee R. Maulik Namwoo Kang PINN AI4CE 18 17 0 05 Jan 2024
Physics-Informed Neural Networks for High-Frequency and Multi-Scale Problems using Transfer Learning Abdul Hannan Mustajab Hao Lyu Z. Rizvi Frank Wuttke AI4CE PINN 8 9 0 05 Jan 2024
Integration of physics-informed operator learning and finite element method for parametric learning of partial differential equations Shahed Rezaei Ahmad Moeineddin Michael Kaliske Markus Apel AI4CE 25 4 0 04 Jan 2024
PINN surrogate of Li-ion battery models for parameter inference. Part I: Implementation and multi-fidelity hierarchies for the single-particle model M. Hassanaly Peter J. Weddle Ryan N. King Subhayan De Alireza Doostan Corey R. Randall Eric J. Dufek Andrew M. Colclasure Kandler Smith 15 7 0 28 Dec 2023
A conservative hybrid physics-informed neural network method for Maxwell-Ampère-Nernst-Planck equations Cheng Chang Zhouping Xin Tieyong Zeng 13 0 0 10 Dec 2023
Grad-Shafranov equilibria via data-free physics informed neural networks Byoungchan Jang A. Kaptanoglu Rahul Gaur Shaw Pan Matt Landreman W. Dorland PINN 18 2 0 22 Nov 2023
Deep Learning in Deterministic Computational Mechanics L. Herrmann Stefan Kollmannsberger AI4CE PINN 35 0 0 27 Sep 2023
Breaking Boundaries: Distributed Domain Decomposition with Scalable Physics-Informed Neural PDE Solvers Arthur Feeney Zitong Li Ramin Bostanabad Aparna Chandramowlishwaran AI4CE 13 1 0 28 Aug 2023
Solving Forward and Inverse Problems of Contact Mechanics using Physics-Informed Neural Networks T. Şahin M. Danwitz A. Popp PINN 14 19 0 24 Aug 2023
Physics-Informed Boundary Integral Networks (PIBI-Nets): A Data-Driven Approach for Solving Partial Differential Equations Monika Nagy-Huber Volker Roth AI4CE PINN 22 3 0 18 Aug 2023
A Critical Review of Physics-Informed Machine Learning Applications in Subsurface Energy Systems Abdeldjalil Latrach M. L. Malki Misael Morales Mohamed Mehana M. Rabiei PINN AI4CE 16 28 0 06 Aug 2023
Spectral-Bias and Kernel-Task Alignment in Physically Informed Neural Networks Inbar Seroussi Asaf Miron Z. Ringel PINN 32 0 0 12 Jul 2023
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs Zhongkai Hao J. Yao Chang Su Hang Su Ziao Wang ... Zeyu Xia Yichi Zhang Songming Liu Lu Lu Jun Zhu PINN 20 29 0 15 Jun 2023
Towards a Machine-Learned Poisson Solver for Low-Temperature Plasma Simulations in Complex Geometries Ihda Chaerony Siffa M. Becker K. Weltmann J. Trieschmann 19 2 0 13 Jun 2023
Error convergence and engineering-guided hyperparameter search of PINNs: towards optimized I-FENN performance Panos Pantidis Habiba Eldababy Christopher Miguel Tagle M. Mobasher 21 20 0 03 Mar 2023
LSA-PINN: Linear Boundary Connectivity Loss for Solving PDEs on Complex Geometry Jian Cheng Wong P. Chiu C. Ooi M. Dao Yew-Soon Ong AI4CE PINN 13 10 0 03 Feb 2023
Spatio-Temporal Super-Resolution of Dynamical Systems using Physics-Informed Deep-Learning Rajat Arora Ankit Shrivastava AI4CE 25 4 0 08 Dec 2022
Physics-guided Data Augmentation for Learning the Solution Operator of Linear Differential Equations Yemo Li Yiwen Pang Bin Shan AI4CE 18 3 0 08 Dec 2022
Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires J. Dabrowski D. Pagendam J. Hilton Conrad Sanderson Dan MacKinlay C. Huston Andrew Bolt Petra Kuhnert PINN 18 16 0 02 Dec 2022
On the Compatibility between Neural Networks and Partial Differential Equations for Physics-informed Learning Kuangdai Leng Jeyan Thiyagalingam PINN 9 2 0 01 Dec 2022
Physics-informed Neural Networks with Unknown Measurement Noise Philipp Pilar Niklas Wahlström PINN 18 6 0 28 Nov 2022
Scaling transformation of the multimode nonlinear Schrödinger equation for physics-informed neural networks I. Chuprov D. Efremenko Jiexing Gao P. Anisimov V. Zemlyakov 11 0 0 29 Sep 2022
On Physics-Informed Neural Networks for Quantum Computers Stefano Markidis PINN 29 18 0 28 Sep 2022
Gradient-Enhanced Physics-Informed Neural Networks for Power Systems Operational Support M. Mohammadian K. Baker Ferdinando Fioretto PINN AI4CE 11 21 0 21 Jun 2022
Physical Activation Functions (PAFs): An Approach for More Efficient Induction of Physics into Physics-Informed Neural Networks (PINNs) J. Abbasi Paal Ostebo Andersen PINN AI4CE 19 13 0 29 May 2022
Auto-PINN: Understanding and Optimizing Physics-Informed Neural Architecture Yicheng Wang Xiaotian Han Chia-Yuan Chang Daochen Zha U. Braga-Neto Xia Hu PINN AI4CE 9 23 0 27 May 2022
Hyper-parameter tuning of physics-informed neural networks: Application to Helmholtz problems Paul Escapil-Inchauspé G. A. Ruz 24 32 0 13 May 2022
Do ReLU Networks Have An Edge When Approximating Compactly-Supported Functions? Anastasis Kratsios Behnoosh Zamanlooy MLT 49 3 0 24 Apr 2022
Improved Training of Physics-Informed Neural Networks with Model Ensembles Katsiaryna Haitsiukevich Alexander Ilin PINN 22 23 0 11 Apr 2022
Physics-informed neural networks for non-Newtonian fluid thermo-mechanical problems: an application to rubber calendering process Thi Nguyen Khoa Nguyen T. Dairay Raphael Meunier Mathilde Mougeot PINN AI4CE 67 29 0 31 Jan 2022
Asymptotic self-similar blow-up profile for three-dimensional axisymmetric Euler equations using neural networks Yao Wang Chen Lai J. Gómez-Serrano T. Buckmaster 14 17 0 18 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 18 1,162 0 14 Jan 2022
Enhancing Computational Fluid Dynamics with Machine Learning Ricardo Vinuesa Steven L. Brunton AI4CE 98 353 0 05 Oct 2021
Learning in Sinusoidal Spaces with Physics-Informed Neural Networks Jian Cheng Wong C. Ooi Abhishek Gupta Yew-Soon Ong AI4CE PINN SSL 16 76 0 20 Sep 2021
A Deep Learning-Based Particle-in-Cell Method for Plasma Simulations Xavier Aguilar Stefano Markidis 13 16 0 05 Jul 2021
MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework C. Jiang S. Esmaeilzadeh Kamyar Azizzadenesheli K. Kashinath Mustafa A. Mustafa H. Tchelepi P. Marcus P. Prabhat Anima Anandkumar AI4CE 182 140 0 01 May 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 117 506 0 11 Mar 2020