= Gareth Roberts
{c}
<Gareth Roberts> studies <Markov chain Monte Carlo> and the mathematical efficiency of Bayesian computation. With <Giacomo Zanella>, he developed importance tempering for high-dimensional sampling.<Scalable Importance Tempering and Bayesian Variable Selection by Giacomo Zanella and Gareth Roberts>[Author byline and abstract]{ref}
Their <Tempered Gibbs sampler> changes how coordinates are selected. Its invariant law differs from the intended target, so <importance sampling> weights correct the averages. This trades easier movement through the state space against the variability of the correcting weights, with explicit theoretical comparisons to ordinary sampling methods.<Scalable Importance Tempering and Bayesian Variable Selection by Giacomo Zanella and Gareth Roberts>[Section 2, equations 1–3, Algorithm TGS and Proposition 1]{ref}
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