\dm_csml_event_details UCL ELLIS

Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap


Harita Dellaporta


University of Warwick


Friday, 13 May 2022




G08 Sir David Davies LT, UCL Roberts Building, London WC1E 7JE



Event series

DeepMind/ELLIS CSML Seminar Series


Simulator-based models are models for which the likelihood is intractable but simulation of synthetic data is possible. They are often used to describe complex real-world phenomena, and as such can often be misspecified in practice. In this talk, I will present a novel algorithm based on the posterior bootstrap and maximum mean discrepancy estimators. This leads to a highly-parallelisable Bayesian inference algorithm with strong robustness properties. This is demonstrated through an in-depth theoretical study which includes generalisation bounds, frequentist consistency and robustness of our posterior guarantees. The approach is then illustrated on a range of examples including a g-and-k distribution and a toggle-switch model.


Harita is a second-year PhD student at the Warwick CDT in Mathematics & Statistics under the supervision of Prof. Theo Damoulas. Prior to this, Harita obtained an MSc in Computational Statistics & Machine Learning from UCL. Her research focuses on generalised notions of Bayesian inference with emphasis on robustness and model misspecification.