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Physics-informed neural networks

Project description

DOI PyPI version

Physics-informed neural networks package

Welcome to the PML repository for physics-informed neural networks. We will use this repository to disseminate our research in this exciting topic.

Install

To install the stable version just do:

pip install pml-pinn

Develop mode

To install in develop mode, clone this repository and do a pip install:

git clone https://github.com/PML-UCF/pinn.git
cd pinn
pip install -e .

Citing this repository

Please, cite this repository using:

@misc{2019_pinn,
    author    = {Felipe A. C. Viana and Renato G. Nascimento and Yigit Yucesan and Arinan Dourado},
    title     = {Physics-informed neural networks package},
    month     = Aug,
    year      = 2019,
    doi       = {10.5281/zenodo.3356877},
    version   = {0.0.3},
    publisher = {Zenodo},
    url       = {https://github.com/PML-UCF/pinn}
    }

The corresponding reference entry should look like:

F. A. C. Viana, R. G. Nascimento, Y. Yucesan, and A. Dourado, Physics-informed neural networks package, v0.0.3, Aug. 2019. doi:10.5281/zenodo.3356877, URL https://github.com/PML-UCF/pinn.

Publications

Journal papers

Conference papers

Project details


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Files for pml-pinn, version 0.0.3
Filename, size File type Python version Upload date Hashes
Filename, size pml_pinn-0.0.3-py3-none-any.whl (17.1 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size pml-pinn-0.0.3.tar.gz (11.5 kB) File type Source Python version None Upload date Hashes View

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