Loading [MathJax]/jax/output/HTML-CSS/fonts/TeX/fontdata.js
Articles | Volume 13, issue 7
https://doi.org/10.5194/gmd-13-3373-2020
https://doi.org/10.5194/gmd-13-3373-2020
Model description paper
 | 
30 Jul 2020
Model description paper |  | 30 Jul 2020

PDE-NetGen 1.0: from symbolic partial differential equation (PDE) representations of physical processes to trainable neural network representations

Olivier Pannekoucke and Ronan Fablet

Model code and software

opannekoucke/pdenetgen: pde-netgen-GMD (Version 1.0.1) O. Pannekoucke https://doi.org/10.5281/zenodo.3891101

PDE-NetGen Source code O. Pannekoucke https://github.com/opannekoucke/pdenetgen

Download
Short summary
Learning physics from data using a deep neural network is a challenge that requires an...
Share