Professor Mark Girolami (Director, CRiSM) Warwick University
Fri 27 Mar 2015, 14:00 - 15:00
Informatics Forum (IF-2.33)

If you have a question about this talk, please contact: Mary-Clare Mackay (mmackay3)

A reduced-variance approach to Monte Carlo integration is presented, that exploits tools from Gaussian process regression to improve asymptotic convergence rates. The method, called ‘control functionals’, enables efficient, unbiased estimation using un-normalised densities and is well-suited to challenging contemporary applications of Bayesian statistics. Joint work with Chris Oates and Nicolas Chopin.