PINA Tutorials
==============

In this folder we collect useful tutorials in order to understand the principles and the potential of **PINA**.

Getting started with PINA
-------------------------
.. toctree::
   :maxdepth: 3
   :titlesonly:

   `Introduction to PINA for Physics Informed Neural Networks training <tutorials/tutorial1/tutorial.html>`_
   `Introduction to PINA Equation class <tutorials/tutorial12/tutorial.html>`_
   `PINA and PyTorch Lightning, training tips and visualizations <tutorials/tutorial11/tutorial.html>`_
   `Building custom geometries with PINA Location class <tutorials/tutorial6/tutorial.html>`_


Physics Informed Neural Networks
--------------------------------
.. toctree::
   :maxdepth: 3
   :titlesonly:

   `Two dimensional Poisson problem using Extra Features Learning <tutorials/tutorial2/tutorial.html>`_
   `Two dimensional Wave problem with hard constraint <tutorials/tutorial3/tutorial.html>`_
   `Resolution of a 2D Poisson inverse problem <tutorials/tutorial7/tutorial.html>`_
   `Periodic Boundary Conditions for Helmotz Equation <tutorials/tutorial9/tutorial.html>`_
   `Multiscale PDE learning with Fourier Feature Network <tutorials/tutorial13/tutorial.html>`_

Neural Operator Learning
------------------------
.. toctree::
   :maxdepth: 3
   :titlesonly:

   `Two dimensional Darcy flow using the Fourier Neural Operator <tutorials/tutorial5/tutorial.html>`_
   `Time dependent Kuramoto Sivashinsky equation using the Averaging Neural Operator <tutorials/tutorial10/tutorial.html>`_

Supervised Learning
-------------------
.. toctree::
   :maxdepth: 3
   :titlesonly:

   `Unstructured convolutional autoencoder via continuous convolution <tutorials/tutorial4/tutorial.html>`_
   `POD-RBF and POD-NN for reduced order modeling <tutorials/tutorial8/tutorial.html>`_