Metadata-Version: 2.1
Name: linpde-gp
Version: 0.0.1
Summary: Linear PDE Solvers as Gaussian Process Inference
Author-email: Marvin Pförtner <marvin.pfoertner@uni-tuebingen.de>
License: MIT
Project-URL: github, https://github.com/marvinpfoertner/linpde-gp
Keywords: partial-differential-equations,gaussian-processes,probabilistic-numerics,galerkin-method,finite-element-method,collocation-method,spectral-methods
Platform: any
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.10
Requires-Python: <3.11,>=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy (>=1.21.3)
Requires-Dist: scipy (>=1.4)
Requires-Dist: probnum (<0.1.25,>=0.1.24)
Requires-Dist: jax[cpu] (>=0.2.18)
Requires-Dist: matplotlib (>=3.4.3)
Requires-Dist: pykeops (<3.0,>=2.1.1)

# LinPDE-GP: Linear PDE Solvers based on GP Regression

Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"

## Getting Started

### Cloning the Repository

This repository includes Git submodules, so it is best cloned via

```shell
git clone --recurse-submodules git@github.com:marvinpfoertner/linpde-gp.git
```

If you forgot the `--recurse-submodules` flag when cloning, simply run

```shell
git submodule update --init --recursive
```

inside the repository.

### Installing a Full Development Environment

```shell
cd path/to/linpde-gp
pip install -r dev-requirements.txt
```

## Citation

If you use this software, please cite our paper.

```bibtex
@misc{Pfoertner2022LinPDEGP,
  author = {Pf\"ortner, Marvin and Steinwart, Ingo and Hennig, Philipp and Wenger, Jonathan},
  title = {Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers},
  year = {2022},
  publisher = {arXiv},
  doi = {10.48550/arxiv.2212.12474},
  url = {https://arxiv.org/abs/2212.12474}
}
```
