PyTorch Implementation of Physics-informed Neural Networks
This is a simple implementation of the Physics-informed Neural Networks (PINNs) using PyTorch and Tensorflow.
Original Work: Maziar Raissi, Paris Perdikaris, and George Em Karniadakis
Github Repo : https://github.com/maziarraissi/PINNs
@article{raissi2017physicsI, title={Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations}, author={Raissi, Maziar and Perdikaris, Paris and Karniadakis, George Em}, journal={arXiv preprint arXiv:1711.10561}, year={2017} }
@article{raissi2017physicsII, title={Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations}, author={Raissi, Maziar and Perdikaris, Paris and Karniadakis, George Em}, journal={arXiv preprint arXiv:1711.10566}, year={2017} }
Major Dependencies:
pip install --upgrade tensorflow
pip install jupyterlab
(JupyterLab) or pip install notebook
Peripheral Dependencies:
pip install numpy
pip install seaborn
pip install matplotlib
pip install pyDOE