Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next

14 January 2022

S. Cuomo

Vincenzo Schiano Di Cola

Papers citing "Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next"

50 / 105 papers shown

Title
Operator Learning for Schrödinger Equation: Unitarity, Error Bounds, and Time Generalization Yash Patel Unique Subedi Ambuj Tewari 31 0 0 23 May 2025
A brief review of the Deep BSDE method for solving high-dimensional partial differential equations Jiequn Han Arnulf Jentzen Weinan E AI4CE 43 0 0 07 May 2025
Reducing Smoothness with Expressive Memory Enhanced Hierarchical Graph Neural Networks Thomas Bailie Yun Sing Koh S. Karthik Mukkavilli V. Vetrova AI4TS 148 0 0 01 Apr 2025
Shape Modeling of Longitudinal Medical Images: From Diffeomorphic Metric Mapping to Deep Learning Edwin Tay Nazli Tümer Amir A. Zadpoor MedIm 152 0 0 27 Mar 2025
Solving 2-D Helmholtz equation in the rectangular, circular, and elliptical domains using neural networks D. Veerababu Prasanta K. Ghosh 85 0 0 26 Mar 2025
High Probability Complexity Bounds of Trust-Region Stochastic Sequential Quadratic Programming with Heavy-Tailed Noise Yuchen Fang Javad Lavaei Katya Scheinberg 66 0 0 24 Mar 2025
ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning Nilo Schwencke Cyril Furtlehner 114 1 0 14 Dec 2024
Multi-Parameter Molecular MRI Quantification using Physics-Informed Self-Supervised Learning Alex Finkelstein Nikita Vladimirov Moritz Zaiss O. Perlman 51 2 0 10 Nov 2024
TRADE: Transfer of Distributions between External Conditions with Normalizing Flows Stefan Wahl Armand Rousselot Felix Dräxler Ullrich Kothe Ullrich Köthe 98 0 0 25 Oct 2024
Metamizer: a versatile neural optimizer for fast and accurate physics simulations Nils Wandel Stefan Schulz Reinhard Klein PINN AI4CE 69 1 0 10 Oct 2024
Generating Physical Dynamics under Priors Zihan Zhou Xiaoxue Wang Tianshu Yu DiffM AI4CE 87 0 0 01 Sep 2024
Practical Aspects on Solving Differential Equations Using Deep Learning: A Primer Georgios Is. Detorakis 82 0 0 21 Aug 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
Reduced-Order Neural Operators: Learning Lagrangian Dynamics on Highly Sparse Graphs Hrishikesh Viswanath Yue Chang Julius Berner Julius Berner Peter Yichen Chen Aniket Bera AI4CE 86 2 0 04 Jul 2024
Physics-Informed Multi-Agent Reinforcement Learning for Distributed Multi-Robot Problems Eduardo Sebastián T. Duong Nikolay Atanasov Eduardo Montijano C. Sagüés 90 3 0 30 Dec 2023
Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming Sen Na Michael W. Mahoney 42 8 0 27 May 2022
Improved Training of Physics-Informed Neural Networks with Model Ensembles Katsiaryna Haitsiukevich Alexander Ilin PINN 75 24 0 11 Apr 2022
Certified machine learning: A posteriori error estimation for physics-informed neural networks Birgit Hillebrecht B. Unger PINN 39 15 0 31 Mar 2022
Error estimates for physics informed neural networks approximating the Navier-Stokes equations Tim De Ryck Ameya Dilip Jagtap S. Mishra PINN 79 115 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 128 200 0 14 Mar 2022
Learning To Estimate Regions Of Attraction Of Autonomous Dynamical Systems Using Physics-Informed Neural Networks Cody Scharzenberger Joe Hays 52 3 0 18 Nov 2021
Solving Partial Differential Equations with Point Source Based on Physics-Informed Neural Networks Xiang Huang Hongsheng Liu Beiji Shi Zidong Wang Kan Yang ... Jing Zhou Fan Yu Bei Hua Lei Chen Bin Dong 54 20 0 02 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 46 210 0 29 Oct 2021
Learning in Sinusoidal Spaces with Physics-Informed Neural Networks Jian Cheng Wong C. Ooi Abhishek Gupta Yew-Soon Ong AI4CE PINN SSL 39 79 0 20 Sep 2021
U-FNO -- An enhanced Fourier neural operator-based deep-learning model for multiphase flow Gege Wen Zong-Yi Li Kamyar Azizzadenesheli Anima Anandkumar S. Benson AI4CE 52 374 0 03 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 84 626 0 02 Sep 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 64 216 0 16 Jul 2021
IDRLnet: A Physics-Informed Neural Network Library Wei Peng Jun Zhang Weien Zhou Xiaoyu Zhao Wen Yao Xiaoqian Chen PINN AI4CE 57 15 0 09 Jul 2021
Error analysis for physics informed neural networks (PINNs) approximating Kolmogorov PDEs Tim De Ryck Siddhartha Mishra PINN 55 100 0 28 Jun 2021
Physics-informed neural networks (PINNs) for fluid mechanics: A review Shengze Cai Zhiping Mao Zhicheng Wang Minglang Yin George Karniadakis PINN AI4CE 37 1,152 0 20 May 2021
Distributed Multigrid Neural Solvers on Megavoxel Domains Aditya Balu Sergio Botelho Biswajit Khara Vinay Rao Chinmay Hegde Soumik Sarkar Santi S. Adavani A. Krishnamurthy Baskar Ganapathysubramanian AI4CE 81 11 0 29 Apr 2021
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 99 228 0 26 Apr 2021
On the approximation of functions by tanh neural networks Tim De Ryck S. Lanthaler Siddhartha Mishra 46 138 0 18 Apr 2021
Conditional physics informed neural networks A. Kovacs L. Exl Alexander Kornell J. Fischbacher Markus Hovorka ... N. Sakuma Akihito Kinoshita T. Shoji A. Kato T. Schrefl PINN 32 40 0 06 Apr 2021
Elvet -- a neural network-based differential equation and variational problem solver Jack Y. Araz J. C. Criado M. Spannowsky 33 13 0 26 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 120 662 0 20 Mar 2021
The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers? Stefano Markidis PINN 56 185 0 12 Mar 2021
SPINN: Sparse, Physics-based, and partially Interpretable Neural Networks for PDEs A. A. Ramabathiran P. Ramachandran PINN AI4CE 69 77 0 25 Feb 2021
Towards Causal Representation Learning Bernhard Schölkopf Francesco Locatello Stefan Bauer Nan Rosemary Ke Nal Kalchbrenner Anirudh Goyal Yoshua Bengio OOD CML AI4CE 89 320 0 22 Feb 2021
Learning atrial fiber orientations and conductivity tensors from intracardiac maps using physics-informed neural networks Thomas Grandits Simone Pezzuto F. Sahli Costabal P. Perdikaris Thomas Pock Gernot Plank Rolf Krause 13 21 0 22 Feb 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
Will Artificial Intelligence supersede Earth System and Climate Models? C. Irrgang Niklas Boers Maike Sonnewald E. Barnes C. Kadow J. Staneva J. Saynisch‐Wagner AI4Cl AI4CE 37 183 0 22 Jan 2021
HypoSVI: Hypocenter inversion with Stein variational inference and Physics Informed Neural Networks Jonathan D. Smith Zachary E. Ross Kamyar Azizzadenesheli J. Muir 23 38 0 09 Jan 2021
Can Transfer Neuroevolution Tractably Solve Your Differential Equations? Jian Cheng Wong Abhishek Gupta Yew-Soon Ong 50 22 0 06 Jan 2021
Data-driven rogue waves and parameter discovery in the defocusing NLS equation with a potential using the PINN deep learning Li Wang Zhenya Yan 41 81 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 108 127 0 14 Dec 2020
DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation Jungeun Kim Kookjin Lee Dongeun Lee Sheo Yon Jin Noseong Park PINN AI4CE 32 80 0 04 Dec 2020
Physics-Informed Neural Network for Modelling the Thermochemical Curing Process of Composite-Tool Systems During Manufacture S. Niaki E. Haghighat Trevor Campbell Xinglong Li R. Vaziri AI4CE 93 207 0 27 Nov 2020
Theory-guided Auto-Encoder for Surrogate Construction and Inverse Modeling Nanzhe Wang Haibin Chang Dongxiao Zhang AI4CE 53 50 0 17 Nov 2020
Physics Informed Neural Networks for Simulating Radiative Transfer Siddhartha Mishra Roberto Molinaro PINN 47 108 0 25 Sep 2020