Title
Scalable Back-Propagation-Free Training of Optical Physics-Informed Neural Networks Yequan Zhao Xinling Yu Xian Xiao Z. Chen Z. Liu G. Kurczveil R. Beausoleil S. Liu Z. Zhang 49 0 0 17 Feb 2025
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RoPINN: Region Optimized Physics-Informed Neural Networks Haixu Wu Huakun Luo Yuezhou Ma Jianmin Wang Mingsheng Long AI4CE 32 6 0 23 May 2024
Feature Mapping in Physics-Informed Neural Networks (PINNs) Chengxi Zeng T. Burghardt A. Gambaruto 34 1 0 10 Feb 2024
The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks Andrea Bonfanti Giuseppe Bruno Cristina Cipriani 21 7 0 06 Feb 2024
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Preconditioning for Physics-Informed Neural Networks Songming Liu Chang Su J. Yao Zhongkai Hao Hang Su Youjia Wu Jun Zhu AI4CE PINN 25 5 0 01 Feb 2024
A Mathematical Guide to Operator Learning Nicolas Boullé Alex Townsend 29 36 0 22 Dec 2023
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Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 37 207 0 16 Jul 2021
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 69 220 0 26 Apr 2021
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 98 272 0 20 Apr 2021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sifan Wang Hanwen Wang P. Perdikaris 131 437 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 91 125 0 14 Dec 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 117 506 0 11 Mar 2020