emdgroup/baybe
Bayesian Optimization and Design of Experiments
This tool helps scientists, engineers, and researchers efficiently design experiments to find optimal settings for their processes or materials. You provide details about the parameters you can control (like temperature or catalyst type) and what you want to achieve (like maximizing yield or minimizing cost). The tool then suggests the next best experiments to run, helping you quickly home in on the ideal conditions.
439 stars. Used by 1 other package. Available on PyPI.
Use this if you need to optimize a process or material by running experiments and want to intelligently select the most informative next steps rather than trial and error.
Not ideal if your experimental space is very small, you already have extensive data, or you need to perform A/B testing with a large number of options and noisy outcomes.
Stars
439
Forks
68
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 13, 2026
Commits (30d)
0
Dependencies
12
Reverse dependents
1
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