My undergraduate honours project, with other researchers' private code/information removed.
The project's goal is to infer the parameters of complex generative models, when doing so analytically is impractical and/or impossible. which uses Bayesian optimization and Gaussian process regression to calculate an approximate posterior distribution over parameter settings.
For a full overview of the project, see my paper.
Note that this is a cloned version of the full repository - commit history and other git information is not available here.