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PINA/docs/source/_tutorial.rst
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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>`_