2021-07-05 11:18:12 +08:00
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Welcome to idrlnet's documentation!
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===================================
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.. toctree::
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:maxdepth: 2
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user/installation
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user/get_started/tutorial
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user/cite_idrlnet
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user/team
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Features
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--------
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2021-07-16 11:35:43 +08:00
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IDRLnet is a machine learning library on top of `PyTorch <https://pytorch.org/>`_. Use IDRLnet if you need a machine
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learning library that solves both forward and inverse differential equations via physics-informed neural
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2021-07-05 11:18:12 +08:00
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networks (PINN). IDRLnet is a flexible framework inspired by `Nvidia Simnet <https://developer.nvidia.com/simnet>`_.
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IDRLnet supports
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- complex domain geometries without mesh generation. Provided geometries include interval, triangle, rectangle, polygon,
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circle, sphere... Other geometries can be constructed using three boolean operations: union, difference, and
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intersection;
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- sampling in the interior of the defined geometry or on the boundary with given conditions.
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- enables the user code to be structured. Data sources, operations, constraints are all represented by ``Node``. The graph
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will be automatically constructed via label symbols of each node. Getting rid of the explicit construction via
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explicit expressions, users model problems more naturally.
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- solving variational minimization problem;
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- solving integral differential equation;
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- adaptive resampling;
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- recover unknown parameter of PDEs from noisy measurement data.
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API reference
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=============
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If you are looking for usage of a specific function, class or method, please refer to the following part.
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.. toctree::
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:maxdepth: 2
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modules/modules
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Indices and tables
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`
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