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Linked the tutorial in the README file for good form, Changed Titles …
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davidkowalk committed Nov 25, 2024
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Expand Up @@ -5,7 +5,7 @@ A standard implementation (e.g., scikit-learn), however, can accommodate only sm
PHYSBO is highly scalable due to an efficient protocol that employs Thompson sampling, random feature maps, one-rank Cholesky update and automatic hyperparameter tuning. Technical features are described in [COMBO's document](https://github.com/tsudalab/combo/blob/master/docs/combo_document.pdf) and [PHYSBO's report](https://doi.org/10.1016/j.cpc.2022.108405) (open access).
PHYSBO was developed based on [COMBO](https://github.com/tsudalab/combo) for academic use.

## Document
## Documentation

- Stable (master branch)
- [English](https://issp-center-dev.github.io/PHYSBO/manual/master/en/index.html)
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- [English](https://issp-center-dev.github.io/PHYSBO/manual/develop/en/index.html)
- [日本語](https://issp-center-dev.github.io/PHYSBO/manual/develop/ja/index.html)

## Required Packages
## Dependencies

- Python >= 3.6
- No longer tested with Python 3.6
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## Usage

For an introductory tutorial please consult the documentation. ([English](https://issp-center-dev.github.io/PHYSBO/manual/master/en/notebook/tutorial_basic.html) / [日本語](https://issp-center-dev.github.io/PHYSBO/manual/develop/ja/install.html#id2))

['examples/simple.py'](./examples/simple.py) is a simple example.

## Data repository
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