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2.0 KiB
ReStructuredText
78 lines
2.0 KiB
ReStructuredText
:html_theme.sidebar_secondary.remove:
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Welcome to PINA’s documentation!
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=======================================
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.. grid:: 6
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:gutter: 1
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.. grid-item::
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.. image:: index_files/tutorial_13_3.png
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:target: _rst/tutorials/tutorial2/tutorial.html
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.. grid-item::
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.. image:: index_files/tutorial_32_0.png
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:target: _rst/tutorials/tutorial4/tutorial.html
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.. grid-item::
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.. image:: index_files/tutorial_13_01.png
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:target: _rst/tutorials/tutorial9/tutorial.html
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.. grid-item::
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.. image:: index_files/tutorial_5_0.png
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:target: _rst/tutorials/tutorial10/tutorial.html
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.. grid-item::
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.. image:: index_files/tutorial_15_0.png
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:target: _rst/tutorials/tutorial13/tutorial.html
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.. grid-item::
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.. image:: index_files/tutorial_36_0.png
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:target: _rst/tutorials/tutorial6/tutorial.html
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.. grid:: 1 1 3 3
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.. grid-item::
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:columns: 12 12 8 8
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Physics Informed Neural network for Advanced modeling (**PINA**) is
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an open-source Python library providing an intuitive interface for
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solving differential equations using PINNs, NOs or both together.
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Based on `PyTorch <https://pytorch.org/>`_ and `PyTorchLightning <https://lightning.ai/docs/pytorch/stable/>`_, **PINA** offers a simple and intuitive way to formalize a specific (differential) problem
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and solve it using neural networks . The approximated solution of a differential equation
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can be implemented using PINA in a few lines of code thanks to the intuitive and user-friendly interface.
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For further information or questions about **PINA** contact us by email.
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.. grid-item-card:: Contents
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:class-title: sd-fs-5
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:class-body: sd-pl-4
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.. toctree::
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:maxdepth: 1
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Installing <_rst/_installation>
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Tutorial <_rst/_tutorial>
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API <_rst/_code>
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Team & Foundings <_team.rst>
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Contributing <_rst/_contributing>
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License <_LICENSE.rst>
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Cite PINA <_cite.rst>
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