v1v2v3 (latest)

PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks

1 February 2024

ArXiv (abs)PDF HTML Github (308★)

Papers citing "PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks"

32 / 32 papers shown

Title
Mollifier Layers: Enabling Efficient High-Order Derivatives in Inverse PDE Learning Ananyae Kumar Bhartari Vinayak Vinayak Vivek B Shenoy AI4CE 190 0 0 16 May 2025
EquiNO: A Physics-Informed Neural Operator for Multiscale Simulations Hamidreza Eivazi Jendrik-Alexander Tröger Stefan H. A. Wittek Stefan Hartmann Andreas Rausch AI4CE 95 0 0 27 Mar 2025
Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases Madison Cooley Varun Shankar Robert M. Kirby Shandian Zhe 87 2 0 04 Oct 2024
Deep Learning Alternatives of the Kolmogorov Superposition Theorem Leonardo Ferreira Guilhoto P. Perdikaris 94 7 0 02 Oct 2024
KAN: Kolmogorov-Arnold Networks Ziming Liu Yixuan Wang Sachin Vaidya Fabian Ruehle James Halverson Marin Soljacic Thomas Y. Hou Max Tegmark 245 563 0 30 Apr 2024
An Expert's Guide to Training Physics-informed Neural Networks Sizhuang He Shyam Sankaran Hanwen Wang P. Perdikaris PINN 90 107 0 16 Aug 2023
About optimal loss function for training physics-informed neural networks under respecting causality V. A. Es'kin Danil V. Davydov Ekaterina D. Egorova Alexey O. Malkhanov Mikhail A. Akhukov Mikhail E. Smorkalov PINN 89 7 0 05 Apr 2023
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks Chen-Chun Wu Min Zhu Qinyan Tan Yadhu Kartha Lu Lu 86 377 0 21 Jul 2022
Respecting causality is all you need for training physics-informed neural networks Sizhuang He Shyam Sankaran P. Perdikaris PINN CML AI4CE 143 203 0 14 Mar 2022
High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach A. Blattmann Dominik Lorenz Patrick Esser Bjorn Ommer 3DV 466 15,665 0 20 Dec 2021
One-Shot Transfer Learning of Physics-Informed Neural Networks Shaan Desai M. Mattheakis H. Joy P. Protopapas Stephen J. Roberts PINN AI4CE 66 58 0 21 Oct 2021
Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks Suryanarayana Maddu D. Sturm Christian L. Müller I. Sbalzarini AI4CE 71 83 0 02 Jul 2021
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 121 234 0 26 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 55 44 0 06 Apr 2021
$NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework$ 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 130 128 0 14 Dec 2020
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 500 2,444 0 18 Oct 2020
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism L. McClenny U. Braga-Neto PINN 84 459 0 07 Sep 2020
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 141 916 0 28 Jul 2020
A Method for Representing Periodic Functions and Enforcing Exactly Periodic Boundary Conditions with Deep Neural Networks S. Dong Naxian Ni 79 137 0 15 Jul 2020
Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks Colby Wight Jia Zhao 77 225 0 09 Jul 2020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating a class of inverse problems for PDEs Siddhartha Mishra Roberto Molinaro PINN 71 266 0 29 Jun 2020
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains Matthew Tancik Pratul P. Srinivasan B. Mildenhall Sara Fridovich-Keil N. Raghavan Utkarsh Singhal R. Ramamoorthi Jonathan T. Barron Ren Ng 124 2,440 0 18 Jun 2020
Array Programming with NumPy Charles R. Harris K. Millman S. Walt R. Gommers Pauli Virtanen ... Tyler Reddy Warren Weckesser Hameer Abbasi C. Gohlke T. Oliphant 156 14,986 0 18 Jun 2020
Implicit Neural Representations with Periodic Activation Functions Vincent Sitzmann Julien N. P. Martel Alexander W. Bergman David B. Lindell Gordon Wetzstein AI4TS 165 2,571 0 17 Jun 2020
Transfer learning based multi-fidelity physics informed deep neural network S. Chakraborty PINN OOD AI4CE 72 165 0 19 May 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 168 538 0 11 Mar 2020
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 248 2,150 0 08 Oct 2019
Physics Informed Extreme Learning Machine (PIELM) -- A rapid method for the numerical solution of partial differential equations Vikas Dwivedi Balaji Srinivasan PINN 61 193 0 08 Jul 2019
$Transfer learning enhanced physics informed neural network for phase-field modeling of fracture$ Transfer learning enhanced physics informed neural network for phase-field modeling of fracture S. Goswami C. Anitescu S. Chakraborty Timon Rabczuk PINN 78 610 0 04 Jul 2019
On the Universality of Invariant Networks Haggai Maron Ethan Fetaya Nimrod Segol Y. Lipman OOD 155 240 0 27 Jan 2019
On the Spectral Bias of Neural Networks Nasim Rahaman A. Baratin Devansh Arpit Felix Dräxler Min Lin Fred Hamprecht Yoshua Bengio Aaron Courville 154 1,451 0 22 Jun 2018
Identity Mappings in Deep Residual Networks Kaiming He Xinming Zhang Shaoqing Ren Jian Sun 354 10,192 0 16 Mar 2016