# Compositionally-Restricted Attention-Based Network (CrabNet)

This software package implements the Compositionally-Restricted Attention-Based Network (`CrabNet`) that takes only composition information to predict material properties.
Additionally, it demonstrates several model interpretability techniques that are possible with `CrabNet`.



## Table of Contents
* Publications / How to cite
* Installation and basic use of `CrabNet`
* Model interpretability with `CrabNet`
* Maintainers



## Publications / How to cite

This repository contains the code accompanying two `CrabNet` publications. Please consider citing them if you want to use `CrabNet` or the techniques discussed within the works:

1. **The "CrabNet publication":** A. Y.-T. Wang, S. K. Kauwe, R. J. Murdock, T. D. Sparks, Compositionally restricted attention-based network for materials property predictions, *npj Comput. Mater.*, **2021**, *7: 77*. DOI: [10.1038/s41524-021-00545-1](https://doi.org/10.1038/s41524-021-00545-1).
1. **The "ExplainableGap publication":** A. Y.-T. Wang, M. S. Mahmoud, M. Czasny, A. Gurlo, CrabNet for Explainable Deep Learning in Materials Science: Bridging the Gap Between Academia and Industry, *Integr. Mater. Manuf. Innov.*, **2022**, *11 (1)*: 41-56. DOI: [10.1007/s40192-021-00247-y](https://doi.org/10.1007/s40192-021-00247-y).


The references in bibtex form:
```bibtex
@article{Wang2021crabnet,
 author = {Wang, Anthony Yu-Tung and Kauwe, Steven K. and Murdock, Ryan J. and Sparks, Taylor D.},
 year = {2021},
 title = {Compositionally restricted attention-based network for materials property predictions},
 pages = {77},
 volume = {7},
 number = {1},
 doi = {10.1038/s41524-021-00545-1},
 publisher = {{Nature Publishing Group}},
 shortjournal = {npj Comput. Mater.},
 journal = {npj Computational Materials}
}
```

```bibtex
@article{Wang2022explainablegap,
 author = {Wang, Anthony Yu-Tung and Mahmoud, Mahamad Salah and Czasny, Mathias and Gurlo, Aleksander},
 year = {2022},
 title = {CrabNet for Explainable Deep Learning in Materials Science: Bridging the Gap Between Academia and Industry},
 url = {https://doi.org/10.1007/s40192-021-00247-y},
 pages = {41--56},
 volume = {11},
 number = {1},
 shortjournal = {Integr. Mater. Manuf. Innov.},
 journal = {Integrating Materials and Manufacturing Innovation},
 doi = {10.1007/s40192-021-00247-y},
 publisher = {{Springer International Publishing AG}}
}
```



## Installation and basic use of `CrabNet`
For the steps, please see the readme located at [README_CrabNet.md](README_CrabNet.md).



## Model interpretability with `CrabNet`
For the steps, please see the readme located at [README_ExplainableGap.md](README_ExplainableGap.md).



## Maintainers
* [`sgbaird`](https://github.com/sgbaird), Sterling Baird (main maintainer)
* [`anthony-wang`](https://github.com/anthony-wang), Anthony Wang