This is the repository for the implementation of the paper Multi-fidelity Bayesian Optimization with Multiple Information Sources of Input-dependent Fidelity, which was accepted as a conference paper in UAI 2024 link to be uploaded.
Please check the experiment folder for the runnable examplar code and corresponding data.
To utilize the code, one needs to specify the target function, the surrogate model used, the acquisition function utilized, and finally
the experiment class. In the experiment/real_exp.py file we have an example code for running our/benchmark methods and how to combine these configurations.
For the required packages, please see the requirement.txt for the prerequisite packages or simply use
pip install requirements.txt
