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.
| Description | Tutorial |
|---|---|
| Introduction to PINA for Physics Informed Neural Networks training | [.ipynb, .py, .html] |
Introduction to PINA Equation class |
[.ipynb, .py, .html] |
| PINA and PyTorch Lightning, training tips and visualizations | [.ipynb, .py, .html] |
Building custom geometries with PINA Location class |
[.ipynb, .py, .html] |
| 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] |
| Multiscale PDE learning with Fourier Feature Network | [.ipynb, .py, .html] |
| 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] |
| Description | Tutorial |
|---|---|
| Unstructured convolutional autoencoder via continuous convolution | [.ipynb, .py, .html] |
| POD-RBF and POD-NN for reduced order modeling | [.ipynb, .py, .html] |
| POD-RBF for modelling Lid Cavity | [.ipynb, .py, .html] |