Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)
You can download this repo and run the demo tasks on your computing machine.
This tool is developed in Fluid Dynamics department, Institute of High Performance Computing (IHPC), A*STAR.
The copyright holder for this project is Fluid Dynamics department, Institute of High Performance Computing (IHPC), A*STAR.
All rights reserved.
Pao-Hsiung Chiu, Jian Cheng Wong*, Chinchun Ooi, My Ha Dao, Yew-Soon Ong (2022), "CAN-PINN: A fast physics-informed neural network based on coupled-automatic-numerical differentiation method", Computer Methods in Applied Mechanics and Engineering, Vol. 395, 114909:1-24. (https://doi.org/10.1016/j.cma.2022.114909)