BayBE: A Bayesian Back End for Experimental Planning in the Low-To-No-Data Regime

This repository contains figures, data and code to reproduce the results from the publication.

Installation

The exact state of required dependencies is stored in requirements.txt.

To run a notebook:

Create a Python 3.10 environment, e.g. via

mamba create --yes --name baybe-paper python=3.10
mamba activate baybe-paper

Install ipykernel and add the kernel to jupyter kernels:

pip install ipykernel==6.29.5
python -m ipykernel install --user --name=baybe-paper --display-name "BayBE Paper"

Select the kernel when running the jupyter notebook. All required dependencies are synced at the start of each notebook.