Metadata-Version: 2.1
Name: pyinn
Version: 0.1.0
Summary: Interpolating Neural Networks
Author: Chanwook Park
Author-email: chanwookpark2024@u.northwestern.edu
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

![INN](/Figure1.png)


## Interpolating Neural Network

This is the github repo for the paper ["Interpolating neural network (INN): A novel unification of machine learning and interpolation theory"](https://arxiv.org/abs/2404.10296).

INN is a lightweight yet precise network architecture that can replace MLPs for data training, partial differential equation (PDE) solving, and parameter calibration. The key features of INNs are:

* Less trainable parameters than MLP without sacrificing accuracy
* Faster and proven convergent behavior
* Fully differntiable and GPU-optimized



## License
This project is licensed under the GNU General Public License v3 - see the [LICENSE](https://www.gnu.org/licenses/) for details.

## Citations
If you found this library useful in academic or industry work, we appreciate your support if you consider 1) starring the project on Github, and 2) citing relevant papers:

```bibtex
@article{park2024engineering,
  title={Engineering software 2.0 by interpolating neural networks: unifying training, solving, and calibration},
  author={Park, Chanwook and Saha, Sourav and Guo, Jiachen and Zhang, Hantao and Xie, Xiaoyu and Bessa, Miguel A and Qian, Dong and Chen, Wei and Wagner, Gregory J and Cao, Jian and others},
  journal={arXiv preprint arXiv:2404.10296},
  year={2024}
}
```
