Gaussian Processes: Gaussian processes are a class of stochastic regression models and are widely employed in Bayesian optimisation. The key concept of Gaussian processes is to model the objective function as a multivariate normal distribution. A Gaussian process on f is specified by a mean function µ and covariance function or kernel Σ as The mean function determines the expected function value at any location x. The kernel determines the shape of the distribution at each location and the properties of the function's behaviour. The kernel takes two locations x, x ′ as inputs and returns a scalar similarity measure between those two points as output