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# Sphinx build info version 1 | ||
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. | ||
config: 4f5936bce8545e2fedf6cc7f0dbcf300 | ||
config: 663d1aa27c0e8323196fe84bdd285651 | ||
tags: 645f666f9bcd5a90fca523b33c5a78b7 |
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Welcome to i-Melt's documentation! | ||
================================== | ||
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Copyright (2021-2023) C. Le Losq and co. | ||
Copyright (2021-2024) C. Le Losq and co. | ||
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Charles Le Losq, Institut de physique du globe de Paris, University Paris Cité | ||
[email protected] | ||
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Barbara Baldoni, Institut de physique du globe de Paris, University Paris Cité | ||
[email protected] | ||
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Andrew P. Valentine, University of Durham | ||
[email protected] | ||
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i-Melt is a physics-guided neural network model, that combines deep neural networks with physical equations to predict the structural, thermodynamic and dynamic properties of aluminosilicate melts and glasses. | ||
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The project is hosted on `Github <https://github.com/charlesll/i-melt>`_, a `Streamlit web calculator <https://i-melt.streamlit.app/>`_ is available and you can read the papers explaining the model `here <https://doi.org/10.1016/j.gca.2021.08.023>`_ and `here <https://doi.org/10.48550/arXiv.2304.12123>`_! | ||
The project is hosted on `Github <https://github.com/charlesll/i-melt>`_, a `Streamlit web calculator <https://i-melt.streamlit.app/>`_ is available and you can read the papers explaining the model `here <https://doi.org/10.1016/j.gca.2021.08.023>`_ and `there <https://doi.org/10.48550/arXiv.2304.12123>`_! | ||
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.. toctree:: | ||
:maxdepth: 2 | ||
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