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A Bayesian global optimization package for material design | Adaptive Learning | Active Learning

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Bgolearn
Bgolearn

🤝🤝🤝 Please star ⭐️ it for promoting open source projects 🌍 ! Thanks !

if you have any questions or need help, you are welcome to contact me

Source code:

Python package - Bgolearn

Package Document / 手册

see 📒 Bgolearn (Click to view)

Written using Python, which is suitable for operating systems, e.g., Windows/Linux/MAC OS etc.

Cite :

  • Zhang Tong-yi, Cao Bin, Wang Yuanhao, Tian Yuan, Sun Sheng. Bayesian global optimization package for material design [2022SR1481726], 2022, Software copyright, GitHub : github.com/Bin-Cao/Bgolearn.

Installing / 安装

pip install Bgolearn 

Checking / 查看

pip show Bgolearn 

Updating / 更新

pip install --upgrade Bgolearn

Update log / 日志

Before version 2.1, it belonged to function building

Bgolearn V2.1.1 Jun 9, 2023. para noise_std By default, the built-in Gaussian process model estimates the noise of the input dataset by maximum likelihood, and yields in a more robust model.

References / 参考文献

See : papers

About / 更多

Maintained by Bin Cao. Please feel free to open issues in the Github or contact Bin Cao ([email protected]) in case of any problems/comments/suggestions in using the code.

Contributing / 共建

Contribution and suggestions are always welcome. In addition, we are also looking for research collaborations. You can submit issues for suggestions, questions, bugs, and feature requests, or submit pull requests to contribute directly. You can also contact the authors for research collaboration.

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