So here are some of the resources for Bayesian optimisation (the actual optimisation process) and Gaussian processes (the way we “estimate” the function we don’t know about to be used with BO):

  • BO book, quite detailed (Ch 1-3 for Gaussian processes, around Ch 7 for BO methods): https://bayesoptbook.com/book/bayesoptbook.pdf

  • BO lecture notes, Chapters 5 to 7 may be relevant (can skip Ch 6.3 tho): https://www.robots.ox.ac.uk/~twgr/teaching/

  • More practical tutorial for BO based on BoTorch library (our BO methods are all implemented using this library): https://botorch.org/docs/tutorials/closed_loop_botorch_only/