CAN-PINN: A Fast Physics-Informed Neural Network Based on
Coupled-Automatic-Numerical Differentiation Method

CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method

29 October 2021

Jian Cheng Wong

Papers citing "CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method"

17 / 17 papers shown

Title
$Neural refractive index field: Unlocking the Potential of Background-oriented Schlieren Tomography in Volumetric Flow Visualization$ Neural refractive index field: Unlocking the Potential of Background-oriented Schlieren Tomography in Volumetric Flow Visualization Yuanzhe He Y. Zheng Shijie Xu Chang Liu Di Peng Yingzheng Liu Weiwei Cai AI4CE 21 0 0 23 Sep 2024
Harnessing physics-informed operators for high-dimensional reliability analysis problems N Navaneeth Tushar Souvik Chakraborty AI4CE 32 0 0 07 Sep 2024
Automatic Differentiation is Essential in Training Neural Networks for Solving Differential Equations Chuqi Chen Yahong Yang Yang Xiang Wenrui Hao 26 2 0 23 May 2024
Data-Driven Physics-Informed Neural Networks: A Digital Twin Perspective Sunwoong Yang Hojin Kim Y. Hong K. Yee R. Maulik Namwoo Kang PINN AI4CE 18 17 0 05 Jan 2024
Adversarial Training for Physics-Informed Neural Networks Yao Li Shengzhu Shi Zhichang Guo Boying Wu AAML PINN 25 0 0 18 Oct 2023
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 18 9 0 08 Oct 2023
Temporal Difference Learning for High-Dimensional PIDEs with Jumps Liwei Lu Hailong Guo Xueqing Yang Yi Zhu AI4CE 13 6 0 06 Jul 2023
ParticleWNN: a Novel Neural Networks Framework for Solving Partial Differential Equations Yaohua Zang Gang Bao 24 4 0 21 May 2023
Physics-informed Neural Networks with Periodic Activation Functions for Solute Transport in Heterogeneous Porous Media Salah A. Faroughi Ramin Soltanmohammad Pingki Datta S. K. Mahjour S. Faroughi 13 22 0 17 Dec 2022
Design of Turing Systems with Physics-Informed Neural Networks J. Kho W. Koh Jian Cheng Wong P. Chiu C. Ooi DiffM AI4CE 19 2 0 24 Nov 2022
Robustness of Physics-Informed Neural Networks to Noise in Sensor Data Jian Cheng Wong P. Chiu C. Ooi My Ha Da 27 3 0 22 Nov 2022
A Curriculum-Training-Based Strategy for Distributing Collocation Points during Physics-Informed Neural Network Training Marcus Münzer C. Bard 10 4 0 21 Nov 2022
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 27 48 0 14 Nov 2022
Learning in Sinusoidal Spaces with Physics-Informed Neural Networks Jian Cheng Wong C. Ooi Abhishek Gupta Yew-Soon Ong AI4CE PINN SSL 16 76 0 20 Sep 2021
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 69 222 0 26 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 131 438 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 91 126 0 14 Dec 2020