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2007.04542
Cited By
Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks
Communications in Computational Physics (Commun. Comput. Phys.), 2020
9 July 2020
Colby Wight
Jia Zhao
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Papers citing
"Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks"
50 / 103 papers shown
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Self-adaptive weighting and sampling for physics-informed neural networks
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178
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Auto-Adaptive PINNs with Applications to Phase Transitions
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Woojeong Kim
243
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AB-PINNs: Adaptive-Basis Physics-Informed Neural Networks for Residual-Driven Domain Decomposition
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Wael H. Ali
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187
1
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10 Oct 2025
Equivariant U-Shaped Neural Operators for the Cahn-Hilliard Phase-Field Model
Xiao Xue
Marco F.P. ten Eikelder
Tianyue Yang
Yiqing Li
Kan He
Shuo Wang
Peter V. Coveney
248
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01 Sep 2025
PIANO: Physics Informed Autoregressive Network
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Jephte Abijuru
Phil Ostheimer
Matthias Kirchler
Sophie Fellenz
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245
1
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22 Aug 2025
Intelligent Sampling of Extreme-Scale Turbulence Datasets for Accurate and Efficient Spatiotemporal Model Training
Wesley Brewer
Murali Meena Gopalakrishnan
Matthias Maiterth
Aditya Kashi
J. Choi
...
P.K. Yeung
Daniel Dotson
Rohini Uma-Vaideswaran
Sarp Oral
Feiyi Wang
297
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05 Aug 2025
Simulating Three-dimensional Turbulence with Physics-informed Neural Networks
Sifan Wang
Shyam Sankaran
Xiantao Fan
P. Stinis
P. Perdikaris
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244
12
0
11 Jul 2025
Over-PINNs: Enhancing Physics-Informed Neural Networks via Higher-Order Partial Derivative Overdetermination of PDEs
Wenxuan Huo
Qiang He
Gang Zhu
Weifeng Huang
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238
0
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A comprehensive analysis of PINNs: Variants, Applications, and Challenges
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Akarsh K Nair
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228
3
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28 May 2025
Scientific machine learning in Hydrology: a unified perspective
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136
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Learning and Transferring Physical Models through Derivatives
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Andrea Cossu
Davide Bacciu
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474
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Reliable and efficient inverse analysis using physics-informed neural networks with normalized distance functions and adaptive weight tuning
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Mitsuteru Asai
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679
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25 Apr 2025
BO-SA-PINNs: Self-adaptive physics-informed neural networks based on Bayesian optimization for automatically designing PDE solvers
Rui Zhang
Liang Li
Stéphane Lanteri
Hao Kang
Jiaqi Li
280
1
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14 Apr 2025
Integral regularization PINNs for evolution equations
Xiaodong Feng
Haojiong Shangguan
Tao Tang
Xiaoliang Wan
PINN
321
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31 Mar 2025
Solving 2-D Helmholtz equation in the rectangular, circular, and elliptical domains using neural networks
Journal of Sound and Vibration (JSV), 2025
D. Veerababu
Prasanta K. Ghosh
250
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26 Mar 2025
Machine learning for modelling unstructured grid data in computational physics: a review
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Sibo Cheng
Marc Bocquet
Weiping Ding
Tobias S. Finn
Rui Fu
...
Yong Zeng
Mingrui Zhang
Hao Zhou
Kewei Zhu
Rossella Arcucci
PINN
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600
24
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13 Feb 2025
Gradient Alignment in Physics-informed Neural Networks: A Second-Order Optimization Perspective
Sizhuang He
Ananyae Kumar Bhartari
Bowen Li
P. Perdikaris
PINN
519
48
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02 Feb 2025
Learn Singularly Perturbed Solutions via Homotopy Dynamics
Chuqi Chen
Yahong Yang
Yang Xiang
Wenrui Hao
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462
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01 Feb 2025
SPIKANs: Separable Physics-Informed Kolmogorov-Arnold Networks
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Amanda A. Howard
P. Stinis
249
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A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural Network Training on Solving Partial Differential Equations
Shu Liu
Stanley Osher
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396
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From PINNs to PIKANs: Recent Advances in Physics-Informed Machine Learning
Juan Diego Toscano
Vivek Oommen
Alan John Varghese
Zongren Zou
Nazanin Ahmadi Daryakenari
Chenxi Wu
George Karniadakis
PINN
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335
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17 Oct 2024
An End-to-End Deep Learning Method for Solving Nonlocal Allen-Cahn and Cahn-Hilliard Phase-Field Models
Yuwei Geng
Olena Burkovska
L. Ju
Guannan Zhang
M. Gunzburger
231
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11 Oct 2024
HyResPINNs: A Hybrid Residual Physics-Informed Neural Network Architecture Designed to Balance Expressiveness and Trainability
Madison Cooley
Robert M. Kirby
Shandian Zhe
Varun Shankar
PINN
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312
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0
04 Oct 2024
Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases
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Varun Shankar
Robert M. Kirby
Shandian Zhe
389
7
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04 Oct 2024
ASPINN: An asymptotic strategy for solving singularly perturbed differential equations
Sen Wang
Peizhi Zhao
Tao Song
391
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General-Kindred Physics-Informed Neural Network to the Solutions of Singularly Perturbed Differential Equations
The Physics of Fluids (Phys. Fluids), 2024
Sen Wang
Peizhi Zhao
Qinglong Ma
Tao Song
PINN
238
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27 Aug 2024
PinnDE: Physics-Informed Neural Networks for Solving Differential Equations
Jason Matthews
Alex Bihlo
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395
3
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19 Aug 2024
Regime-Aware Time Weighting for Physics-Informed Neural Networks
Gabriel Turinici
261
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Finite basis Kolmogorov-Arnold networks: domain decomposition for data-driven and physics-informed problems
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Ashish S. Nair
Sarah H. Murphy
Alexander Heinlein
P. Stinis
AI4CE
540
41
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28 Jun 2024
An Advanced Physics-Informed Neural Operator for Comprehensive Design Optimization of Highly-Nonlinear Systems: An Aerospace Composites Processing Case Study
Milad Ramezankhani
A. Deodhar
Rishi Parekh
Dagnachew Birru
AI4CE
281
18
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20 Jun 2024
Adapting Physics-Informed Neural Networks to Improve ODE Optimization in Mosquito Population Dynamics
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D. V. Cuong
Branislava Lalić
Mina Petrić
Binh Nguyen
M. Roantree
PINN
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364
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07 Jun 2024
Discovering Physics-Informed Neural Networks Model for Solving Partial Differential Equations through Evolutionary Computation
Swarm and Evolutionary Computation (Swarm Evol. Comput.), 2024
Bo Zhang
Chao Yang
PINN
342
8
0
18 May 2024
Gradient Flow Based Phase-Field Modeling Using Separable Neural Networks
Computer Methods in Applied Mechanics and Engineering (CMAME), 2024
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Susanta Ghosh
AI4CE
264
3
0
09 May 2024
Unveiling the optimization process of Physics Informed Neural Networks: How accurate and competitive can PINNs be?
Jorge F. Urbán
P. Stefanou
José A. Pons
PINN
444
65
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07 May 2024
Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations
International Joint Conference on Artificial Intelligence (IJCAI), 2024
Nima Hosseini Dashtbayaz
G. Farhani
Boyu Wang
Charles Ling
384
3
0
02 May 2024
Optimal time sampling in physics-informed neural networks
Gabriel Turinici
PINN
208
3
0
29 Apr 2024
Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes
Ming Zhong
Dehao Liu
Raymundo Arroyave
U. Braga-Neto
AI4CE
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228
2
0
08 Apr 2024
Learning in PINNs: Phase transition, total diffusion, and generalization
Sokratis J. Anagnostopoulos
Juan Diego Toscano
Nikolaos Stergiopulos
George Karniadakis
278
17
0
27 Mar 2024
Parametric Encoding with Attention and Convolution Mitigate Spectral Bias of Neural Partial Differential Equation Solvers
Structural And Multidisciplinary Optimization (SMO), 2024
Mehdi Shishehbor
Shirin Hosseinmardi
Ramin Bostanabad
AI4CE
276
13
0
22 Mar 2024
PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks
Sizhuang He
Bowen Li
Yuhan Chen
P. Perdikaris
AI4CE
PINN
632
98
0
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Binary structured physics-informed neural networks for solving equations with rapidly changing solutions
Journal of Computational Physics (JCP), 2024
Yanzhi Liu
Ruifan Wu
Ying Jiang
PINN
352
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23 Jan 2024
Multifidelity domain decomposition-based physics-informed neural networks and operators for time-dependent problems
Alexander Heinlein
Amanda A. Howard
Damien Beecroft
P. Stinis
AI4CE
294
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15 Jan 2024
Data-Driven Physics-Informed Neural Networks: A Digital Twin Perspective
Sunwoong Yang
Hojin Kim
Y. Hong
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444
59
0
05 Jan 2024
Efficient Discrete Physics-informed Neural Networks for Addressing Evolutionary Partial Differential Equations
Siqi Chen
Bin Shan
Ye Li
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233
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22 Dec 2023
Stacked networks improve physics-informed training: applications to neural networks and deep operator networks
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Sarah H. Murphy
Shady E. Ahmed
P. Stinis
AI4CE
328
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Solving High Frequency and Multi-Scale PDEs with Gaussian Processes
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Madison Cooley
Da Long
Shibo Li
R. Kirby
Shandian Zhe
335
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0
08 Nov 2023
TSONN: Time-stepping-oriented neural network for solving partial differential equations
W. Cao
Weiwei Zhang
AI4TS
216
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Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology
Qingsong Xu
Yilei Shi
Jonathan Bamber
Ye Tuo
Ralf Ludwig
Xiao Xiang Zhu
AI4CE
944
22
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Spectral operator learning for parametric PDEs without data reliance
Computer Methods in Applied Mechanics and Engineering (CMAME), 2023
Junho Choi
Taehyun Yun
Namjung Kim
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244
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03 Oct 2023
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