https://github.com/aspuru-guzik-group/golem
Golem: an algorithm for robust experiment and process optimization
https://github.com/aspuru-guzik-group/golem
experimental-design machine-learning optimization
Last synced: 13 days ago
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Golem: an algorithm for robust experiment and process optimization
- Host: GitHub
- URL: https://github.com/aspuru-guzik-group/golem
- Owner: aspuru-guzik-group
- License: mit
- Created: 2019-10-29T19:16:08.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2021-03-08T23:26:38.000Z (about 4 years ago)
- Last Synced: 2025-04-11T04:04:04.812Z (13 days ago)
- Topics: experimental-design, machine-learning, optimization
- Language: Jupyter Notebook
- Homepage: https://aspuru-guzik-group.github.io/golem/
- Size: 16.2 MB
- Stars: 17
- Watchers: 4
- Forks: 1
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Golem: An algorithm for robust experiment and process optimization
[](https://github.com/aspuru-guzik-group/golem/actions/workflows/ci.yml)
[](https://codecov.io/gh/aspuru-guzik-group/golem)``Golem`` is an algorithm for robust optimization. It can be used in conjunction with any optimization algorithms or
design of experiment strategy of choice. ``Golem`` helps identifying optimal solutions that are robust to input uncertainty,
thus ensuring the reproducible performance of optimized experimental protocols and processes. It can be used to analyze
the robustness of past experiments, or to guide experiment planning algorithms toward robust solutions on the fly. For
more details on the algorithm and its behaviour please refer to the [publication](https://arxiv.org/abs/2103.03716) and
the [documentation](https://aspuru-guzik-group.github.io/golem/).### Installation
``Golem`` can be installed with ``pip``:```
pip install matter-golem
```### Dependencies
The installation requires:
* ``python >= 3.7``
* ``numpy``
* ``scipy >= 1.4``
* ``pandas``
* ``scikit-learn``### Citation
``Golem`` is research software. If you make use of it in scientific publications, please cite the following article:```
@misc{golem,
title={Golem: An algorithm for robust experiment and process optimization},
author={Matteo Aldeghi and Florian Häse and Riley J. Hickman and Isaac Tamblyn and Alán Aspuru-Guzik},
year={2021},
eprint={2103.03716},
archivePrefix={arXiv},
primaryClass={math.OC}
}
```### License
``Golem`` is distributed under an MIT License.