baybe.simulation

Functionality to “simulate” Bayesian DOE given a lookup mechanism.

The term “simulation” can have two slightly different interpretations, depending on the applied context:

• It can refer to “backtesting” a particular DOE strategy on a fixed (finite) dataset. In this context, “simulation” means investigating what experimental trajectory we would have observed had we applied the recommender in a certain defined context and restricted the possible parameter configurations to those contained in the dataset.

• It can refer to the simulation of an actual DOE loop (i.e. recommending experiments and retrieving the corresponding measurements) where the loop closure is realized in the form of a callable (black-box) function that can be queried during the optimization to provide target values.

Modules

core	Core simulation and backtesting functionality.
lookup	Target lookup mechanisms.
scenarios	Batch simulation of multiple campaigns.
transfer_learning	Functionality for transfer learning backtesting.