Metadata-Version: 2.1
Name: MeDIL
Version: 0.5.0
Summary: This package is for causal inference, focusing on the Measurement Dependence Inducing Latent (MeDIL) Causal Model framework.
Home-page: UNKNOWN
Author: Alex Markham
Author-email: alex.markham@causal.dev
License: GNU Affero General Public License v3 or later (AGPLv3+)
Platform: UNKNOWN
Description-Content-Type: text/markdown
Requires-Dist: numpy
Provides-Extra: gan
Requires-Dist: pytorch-lightning ; extra == 'gan'
Provides-Extra: all
Requires-Dist: dcor ; extra == 'all'
Requires-Dist: torch ; extra == 'all'
Requires-Dist: matplotlib ; extra == 'all'
Requires-Dist: networkx ; extra == 'all'
Provides-Extra: dcor
Requires-Dist: dcor ; extra == 'dcor'
Provides-Extra: vis
Requires-Dist: matplotlib ; extra == 'vis'
Requires-Dist: networkx ; extra == 'vis'

## MeDIL
MeDIL is a Python package for causal inference, focusing on the Measurement Dependence Inducing Latent (MeDIL) Causal Model framework[^fn1].

More information can be found in the [documentation](https://medil.causal.dev) or on the [project web page](https://causal.dev/project/medil)

### Support, Bugs, and Conttributing
If you have any questions, suggestions, feedback, or bugs to report, please [open an issue on Gitlab](https://gitlab.com/alex-markham/medil/issues/new) or [on Github](https://github.com/neuroinfo19/medil/issues/new) or [contact me](https://causal.dev/#contact).
Additionally, if you would like to use this package or any of its code in your research, or to contribute to this package, feel free (but not obliged) to [contact me](https://causal.dev/#contact).

### License
See [LICENSE](https://gitlab.com/alex-markham/medil/blob/master/LICENSE.txt), which is the GNU Affero General Public License v3.

### Changelog
See [CHANGELOG](https://gitlab.com/alex-markham/medil/blob/master/CHANGELOG.md) for a history of the already implemented features, works in progress, and future feature ideas.

### References
[^fn1]: Alex Markham and Moritz Grosse-Wentrup (2019). Measurement Dependence Inducing Latent Causal Models. *Conference on Uncertainty in Artificial Intelligence (UAI)*, 2020. ISSN 2640-3498. URL [http://www.auai.org/uai2020/proceedings/244\_main\_paper.pdf.](http://www.auai.org/uai2020/proceedings/244_main_paper.pdf)


