pml-pinn

Physics-informed neural networks


Keywords
physics, informed, neural, networks, machine, learning, deep, tensorflow, keras, python
License
MIT
Install
pip install pml-pinn==0.0.3

Documentation

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