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Bayesian Optimization Structure Search (BOSS) is a general-purpose Bayesian Optimization code. It is designed to facilitate machine learning in computational and experimental natural sciences. See research examples for various applications of BOSS.

For a more detailed description of the code and tutorials, please consult the user guide.

Installation

BOSS is distributed as a PyPI package and can be installed using pip:

python3 -m pip install aalto-boss

We recommend installing BOSS inside a virtual environment (venv, conda…). If you are not using virtual environments, we recommend performing a user-installation instead:

python3 -m pip install --user aalto-boss

Further instructions are provided in the user guide installation section.

Usage

Tutorials to get you started are available in our user guide. Detailed descriptions of how BOSS operates are available in the manual.

Credits

BOSS is under active development in the Materials Informatics Laboratory at the University of Turku and the Computational Electronic Structure Theory (CEST) group at Aalto University. For the full list of authors see BOSS people.

If you wish to use BOSS in your research, please use the citation.

Issues and feature requests

It is strongly encouraged to submit bug reports, questions, and feature requests via the gitlab issue tracker. The BOSS development team can be contacted by email at milica.todorovic@utu.fi

Release files for aalto-boss 1.15.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for aalto-boss 1.15.2
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aalto_boss-1.15.2.tar.gz 126.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for aalto-boss 1.15.2
File Interpreter ABI Platform
aalto_boss-1.15.2-py3-none-any.whl Python 3 none any Details

Total release size: 283.7 kB

Release files / aalto_boss-1.15.2.tar.gz

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Release files / aalto_boss-1.15.2-py3-none-any.whl

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