70 lines
2.3 KiB
ReStructuredText
70 lines
2.3 KiB
ReStructuredText
Welcome to PINA's documentation!
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===================================================
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.. figure:: index_files/pina_logo.png
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:align: center
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:width: 150
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PINA is a Python package providing an easy interface to deal with
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physics-informed neural networks (PINN) for the approximation of (differential,
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nonlinear, ...) functions. Based on Pytorch, PINA offers a simple and intuitive
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way to formalize a specific problem and solve it using PINN. The approximated
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solution of a differential equation can be implemented using PINA in a few lines
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of code thanks to the intuitive and user-friendly interface.
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.. figure:: index_files/API_color.png
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:alt: PINA application program interface
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:align: center
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:width: 500
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Physics-informed neural network
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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PINN is a novel approach that involves neural networks to solve supervised
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learning tasks while respecting any given law of physics described by general
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nonlinear differential equations. Proposed in "Physics-informed neural
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networks: A deep learning framework for solving forward and inverse problems
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involving nonlinear partial differential equations", such framework aims to
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solve problems in a continuous and nonlinear settings. :py:class:`pina.pinn.PINN`
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.. toctree::
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:maxdepth: 2
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:caption: Package Documentation:
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Installation <_rst/installation>
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API <_rst/code>
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Contributing <_rst/contributing>
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License <LICENSE.rst>
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.. the following is demo content intended to showcase some of the features you can invoke in reStructuredText
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.. this can be safely deleted or commented out
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.. ........................................................................................
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.. toctree::
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:maxdepth: 1
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:numbered:
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:caption: Tutorials:
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Getting start with PINA <_rst/tutorial1/tutorial.rst>
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Poisson problem <_rst/tutorial2/tutorial.rst>
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Wave equation <_rst/tutorial3/tutorial.rst>
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Continuous Convolutional Filter <_rst/tutorial4/tutorial.rst>
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Fourier Neural Operator <_rst/tutorial5/tutorial.rst>
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Geometry Usage <_rst/tutorial6/tutorial.rst>
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.. ........................................................................................
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.. toctree::
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:maxdepth: 2
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:numbered:
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:caption: Download
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.. ........................................................................................
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