Overview of initial design strategies for Bayesian optimisation. Implementations in R.
Overview of some functions for testing and benchmarking Bayesian optimisation. Implementations in R.
Surrogate model alternatives to Gaussian processes for Bayesian optimisation. Implementations in R.
A comprehensive overview of acquisition functions for Gaussian processes and Bayesian optimisation. Implementation in R.
A comprehensive overview of kernels, or covariance functions, for Gaussian processes and Bayesian optimisation. Implementation in R.
Developing a bespoke Bayesian model for dose-response screening assays with batch effects
Building bespoke Bayesian models for for dose-response curves in biochemical assays.
Tools and tutorials for Bayesian optimisation.
All the basic components of Bayesian optimisation introduced and implemented in R
Developing a bespoke Bayesian model for fitting the Hill equation in biochemical assays