Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems

1 November 2021

Papers citing "Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems"

50 / 139 papers shown

Title
Challenges in Training PINNs: A Loss Landscape Perspective Pratik Rathore Weimu Lei Zachary Frangella Lu Lu Madeleine Udell AI4CE PINN ODL 44 39 0 02 Feb 2024
Resolution invariant deep operator network for PDEs with complex geometries Jianguo Huang Yue Qiu 30 0 0 01 Feb 2024
PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks Sizhuang He Bowen Li Yuhan Chen P. Perdikaris AI4CE PINN 26 29 0 01 Feb 2024
Speeding up and reducing memory usage for scientific machine learning via mixed precision Joel Hayford Jacob Goldman-Wetzler Eric Wang Lu Lu 49 8 0 30 Jan 2024
Pontryagin Neural Operator for Solving Parametric General-Sum Differential Games Lei Zhang Mukesh Ghimire Zhenni Xu Wenlong Zhang Yi Ren 30 3 0 03 Jan 2024
PINN surrogate of Li-ion battery models for parameter inference. Part II: Regularization and application of the pseudo-2D model M. Hassanaly Peter J. Weddle Ryan N. King Subhayan De Alireza Doostan Corey R. Randall Eric J. Dufek Andrew M. Colclasure Kandler Smith 25 6 0 28 Dec 2023
Hutchinson Trace Estimation for High-Dimensional and High-Order Physics-Informed Neural Networks Zheyuan Hu Zekun Shi George Karniadakis Kenji Kawaguchi AI4CE PINN 49 22 0 22 Dec 2023
A unified framework for learning with nonlinear model classes from arbitrary linear samples Ben Adcock Juan M. Cardenas N. Dexter 34 3 0 25 Nov 2023
An Operator Learning Framework for Spatiotemporal Super-resolution of Scientific Simulations Valentin Duruisseaux Amit Chakraborty AI4CE 16 1 0 04 Nov 2023
Zero Coordinate Shift: Whetted Automatic Differentiation for Physics-informed Operator Learning Kuangdai Leng Mallikarjun Shankar Jeyan Thiyagalingam 31 2 0 01 Nov 2023
Transfer learning for improved generalizability in causal physics-informed neural networks for beam simulations Taniya Kapoor Hongrui Wang Alfredo Núñez R. Dollevoet AI4CE PINN 19 15 0 01 Nov 2023
Adversarial Training for Physics-Informed Neural Networks Yao Li Shengzhu Shi Zhichang Guo Boying Wu AAML PINN 30 0 0 18 Oct 2023
$PMNN:Physical Model-driven Neural Network for solving time-fractional differential equations$ PMNN:Physical Model-driven Neural Network for solving time-fractional differential equations Zhiying Ma Jie Hou Wenhao Zhu Yaxin Peng Ying Li 16 12 0 07 Oct 2023
Deep Learning in Deterministic Computational Mechanics L. Herrmann Stefan Kollmannsberger AI4CE PINN 43 0 0 27 Sep 2023
Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data Wai Tong Chung Bassem Akoush Pushan Sharma Alex Tamkin Kihoon Jung ... D. Brouzet M. Talei B. Savard A. Poludnenko M. Ihme AI4CE 25 13 0 23 Sep 2023
Physics-Informed Neural Networks for an optimal counterdiabatic quantum computation Antonio Ferrer-Sánchez Carlos Flores-Garrigós C. Hernani-Morales José J. Orquín-Marqués N. N. Hegade Alejandro Gomez Cadavid Iraitz Montalban Enrique Solano Yolanda Vives-Gilabert J. D. Martín-Guerrero 32 2 0 08 Sep 2023
Artificial to Spiking Neural Networks Conversion for Scientific Machine Learning Qian Zhang Chen-Chun Wu Adar Kahana Youngeun Kim Yuhang Li George Karniadakis Priyadarshini Panda 30 9 0 31 Aug 2023
Physics informed Neural Networks applied to the description of wave-particle resonance in kinetic simulations of fusion plasmas J. Kumar D. Zarzoso V. Grandgirard Jana Ebert Stefan Kesselheim PINN 22 0 0 23 Aug 2023
An Expert's Guide to Training Physics-informed Neural Networks Sizhuang He Shyam Sankaran Hanwen Wang P. Perdikaris PINN 28 97 0 16 Aug 2023
Learning Specialized Activation Functions for Physics-informed Neural Networks Honghui Wang Lu Lu Shiji Song Gao Huang PINN AI4CE 16 11 0 08 Aug 2023
Introducing Hybrid Modeling with Time-series-Transformers: A Comparative Study of Series and Parallel Approach in Batch Crystallization Niranjan Sitapure J. Kwon 35 32 0 25 Jul 2023
Multi-stage Neural Networks: Function Approximator of Machine Precision Yongjian Wang Ching-Yao Lai 48 36 0 18 Jul 2023
Auxiliary-Tasks Learning for Physics-Informed Neural Network-Based Partial Differential Equations Solving Junjun Yan Xinhai Chen Zhichao Wang Enqiang Zhou Jie Liu PINN AI4CE 29 1 0 12 Jul 2023
Temporal Difference Learning for High-Dimensional PIDEs with Jumps Liwei Lu Hailong Guo Xueqing Yang Yi Zhu AI4CE 23 6 0 06 Jul 2023
Accelerated primal-dual methods with enlarged step sizes and operator learning for nonsmooth optimal control problems Yongcun Song Xiaoming Yuan Hangrui Yue AI4CE 19 2 0 01 Jul 2023
Parameter Identification for Partial Differential Equations with Spatiotemporal Varying Coefficients Guangtao Zhang Yiting Duan Guanyu Pan Qijing Chen Huiyu Yang Zhikun Zhang 17 0 0 30 Jun 2023
Residual-Based Error Corrector Operator to Enhance Accuracy and Reliability of Neural Operator Surrogates of Nonlinear Variational Boundary-Value Problems Prashant K. Jha 32 4 0 21 Jun 2023
ST-PINN: A Self-Training Physics-Informed Neural Network for Partial Differential Equations Junjun Yan Xinhai Chen Zhichao Wang Enqiang Zhoui Jie Liu PINN DiffM AI4CE 25 10 0 15 Jun 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 29 30 0 15 Jun 2023
Efficient Training of Physics-Informed Neural Networks with Direct Grid Refinement Algorithm Shikhar Nilabh F. Grandia 39 1 0 14 Jun 2023
CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions Ben Adcock Juan M. Cardenas N. Dexter 24 6 0 01 Jun 2023
Efficient PDE-Constrained optimization under high-dimensional uncertainty using derivative-informed neural operators Dingcheng Luo Thomas O'Leary-Roseberry Peng Chen Omar Ghattas AI4CE 24 15 0 31 May 2023
CrystalGPT: Enhancing system-to-system transferability in crystallization prediction and control using time-series-transformers Niranjan Sitapure J. Kwon 21 51 0 31 May 2023
Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs Keju Tang Jiayu Zhai Xiaoliang Wan Chao Yang 29 8 0 30 May 2023
ParticleWNN: a Novel Neural Networks Framework for Solving Partial Differential Equations Yaohua Zang Gang Bao 29 4 0 21 May 2023
Deep Learning for Solving and Estimating Dynamic Macro-Finance Models Benjamin Fan Edward Qiao Anran Jiao Zhouzhou Gu Wenhao Li Lu Lu 11 12 0 05 May 2023
Physics-informed radial basis network (PIRBN): A local approximating neural network for solving nonlinear PDEs Jinshuai Bai Guirong Liu Ashish Gupta Laith Alzubaidi Xinzhu Feng Yuantong T. Gu PINN 26 1 0 13 Apr 2023
Maximum-likelihood Estimators in Physics-Informed Neural Networks for High-dimensional Inverse Problems G. S. Gusmão A. Medford PINN 14 8 0 12 Apr 2023
Physics-informed PointNet: On how many irregular geometries can it solve an inverse problem simultaneously? Application to linear elasticity Ali Kashefi Leonidas J. Guibas T. Mukerji PINN 3DPC AI4CE 32 9 0 22 Mar 2023
On the uncertainty analysis of the data-enabled physics-informed neural network for solving neutron diffusion eigenvalue problem Yu Yang Helin Gong Qihong Yang Yangtao Deng Qiaolin He Shiquan Zhang DiffM 40 9 0 15 Mar 2023
Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration Zhongyi Jiang Min Zhu Dongzhuo Li Qiuzi Li Yanhua O. Yuan Lu Lu AI4CE 46 49 0 08 Mar 2023
MetaPhysiCa: OOD Robustness in Physics-informed Machine Learning S Chandra Mouli M. A. Alam Bruno Ribeiro OOD 29 4 0 06 Mar 2023
Physics-informed neural networks for solving forward and inverse problems in complex beam systems Taniya Kapoor Hongrui Wang A. Núñez R. Dollevoet AI4CE PINN 23 46 0 02 Mar 2023
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions Michael Penwarden Ameya Dilip Jagtap Shandian Zhe George Karniadakis Robert M. Kirby PINN AI4CE 23 57 0 28 Feb 2023
The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach Yongcun Song Xiaoming Yuan Hangrui Yue PINN 27 6 0 16 Feb 2023
PINN Training using Biobjective Optimization: The Trade-off between Data Loss and Residual Loss Fabian Heldmann Sarah Treibert Matthias Ehrhardt K. Klamroth 38 20 0 03 Feb 2023
Neural Operator: Is data all you need to model the world? An insight into the impact of Physics Informed Machine Learning Hrishikesh Viswanath Md Ashiqur Rahman Abhijeet Vyas Andrey Shor Beatriz Medeiros Stephanie Hernandez S. Prameela Aniket Bera PINN AI4CE 47 4 0 30 Jan 2023
Deep learning for full-field ultrasonic characterization Yang Xu Fatemeh Pourahmadian Jian Song Congli Wang AI4CE 29 4 0 06 Jan 2023
Physics-Informed Neural Networks for Prognostics and Health Management of Lithium-Ion Batteries Pengfei Wen Z. Ye Yong Li Shaowei Chen Pu Xie Shuai Zhao 30 35 0 02 Jan 2023
Fixed-budget online adaptive learning for physics-informed neural networks. Towards parameterized problem inference T. Nguyen T. Dairay Raphael Meunier Christophe Millet Mathilde Mougeot OOD AI4CE 15 5 0 22 Dec 2022