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StatMixedML authored Oct 27, 2023
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## `Available Distributions`
Our framework is built upon PyTorch and Pyro, enabling users to harness a diverse set of distributional families. XGBoostLSS currently supports the [following distributions](https://statmixedml.github.io/XGBoostLSS/distributions/).

## `How to use`
## `How to Use`
Please visit the [example section](https://statmixedml.github.io/XGBoostLSS/examples/Gaussian_Regression/) for guidance on how to use the framework.

## `Documentation`
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## `Feedback`
We encourage you to provide feedback on how to enhance XGBoostLSS or request the implementation of additional distributions by opening a [new discussion](https://github.com/StatMixedML/XGBoostLSS/discussions).

## `How to cite`
## `How to Cite`
If you use XGBoostLSS in your research, please cite it as:

```bibtex
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