PINA Tutorials
In this folder we collect useful tutorials in order to understand the principles and the potential of PINA. Please read the following table for details about the tutorials. The HTML version of all the tutorials is available also within the documentation.
Getting started with PINA
| Description |
Tutorial |
| Introduction to PINA for Physics Informed Neural Networks training |
[.ipynb, .py, .html] |
Building custom geometries with PINA Location class |
[.ipynb, .py, .html] |
Physics Informed Neural Networks
| Description |
Tutorial |
| Two dimensional Poisson problem using Extra Features Learning |
[.ipynb, .py, .html] |
| Two dimensional Wave problem with hard constraint |
[.ipynb, .py, .html] |
| Resolution of a 2D Poisson inverse problem |
[.ipynb, .py, .html] |
| Periodic Boundary Conditions for Helmotz Equation |
[.ipynb, .py, .html] |
Neural Operator Learning
| Description |
Tutorial |
| Two dimensional Darcy flow using the Fourier Neural Operator |
[.ipynb, .py, .html] |
| Time dependent Kuramoto Sivashinsky equation using the Averaging Neural Operator |
[.ipynb, .py, .html] |
Supervised Learning
| Description |
Tutorial |
| Unstructured convolutional autoencoder via continuous convolution |
[.ipynb, .py, .html] |
| POD-NN for reduced order modeling |
[.ipynb, .py, .html] |
