Speaker
Ameek Malhotra
Description
Cosmological model selection, in the framework of Bayesian
inference requires the calculation of the Bayesian evidence. This can often
be quite challenging, especially if the underlying likelihood function is
expensive to evaluate. I will discuss how a technique called Bayesian
Optimisation, based on Gaussian Process regression, can be used to
calculate this evidence in far fewer likelihood evaluations, offering a much
more efficient approach compared to traditional methods. Parameter
posteriors are also obtained as a by-product of the evidence calculation.
