Archive for Alan Turing Institute

postdoc at Warwick on robust SMC [call]

Posted in Kids, pictures, R, Statistics, University life with tags , , , , , , , , on January 11, 2020 by xi'an

Here is a call for a research fellow at the University of Warwick to work with Adam Johansen and Théo Damoulas on the EPSRC and Lloyds Register Foundaton funded project “Robust Scalable Sequential Monte Carlo with application to Urban Air Quality”. To quote

The position will be based primarily at the Department of Statistics of the University of Warwick. The post holder will work closely in collaboration with the rest of the project team and another postdoctoral researcher to be recruited shortly to work within the Data Centric Engineering programme at the Alan Turing Institute in London. The post holder will be expected to visit the Alan Turing Institute regularly.

Candidates with strong backgrounds in the mathematical analysis of stochastic algorithms or sequential Monte Carlo methods are particularly encouraged to apply. Closing date is 19 Jan 2020.

we need to talk about statistics

Posted in pictures, Statistics, University life with tags , , , , on July 17, 2019 by xi'an

another instance of a summer of Bayesian conferences

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , on March 15, 2018 by xi'an

As it happens, the next MaxEnt conference will happens in London, on 2-6 July, at the Alan Turing Institute, which makes it another perfect continuation of the ISBA meeting in Edinburgh, or of the Computational Statistics summer school in Warwick the week after. But in competition with BAYsm in Warwick and MCqMC in Rennes. I once attended a MaxEnt meeting in Oxford. (Oxford, Mississippi!) Which was quite interesting in the audience it attracted and the focus of the discussions, some of which were exhilaratingly philosophical!

pseudo slice sampling

Posted in Books, Statistics, University life with tags , , , , , on November 26, 2015 by xi'an

The workshop in Warwick last week made me aware of (yet) another arXiv posting I had missed: Pseudo-marginal slice sampling by Iain Murray and Matthew Graham. The idea is to mix the pseudo-marginal approach of Andrieu and Roberts (2009) with a noisy slice sampling scheme à la Neal (2003). The auxiliary random variable u used in the (pseudo-marginal) unbiased estimator of the target I(θ), Î(θ,u), and with distribution q(u) is merged with the random variable of interest so that the joint is


and a Metropolis-Hastings proposal on that target simulating from k(θ,θ’)q(u’) [meaning the auxiliary is simulated independently] recovers the pseudo-marginal Metropolis-Hastings ratio


(which is a nice alternative proof that the method works!). The novel idea in the paper is that the proposal on the auxiliary u can be of a different form, while remaining manageable. For instance, as a two-block Gibbs sampler. Or an elliptical slice sampler for the u component. The argument being that an independent update of u may lead the joint chain to get stuck. Among the illustrations in the paper, an Ising model (with no phase transition issue?) and a Gaussian process applied to the Pima Indian data set (despite a recent prohibition!). From the final discussion, I gather that the modification should be applicable to every (?) case when a pseudo-marginal approach is available, since the auxiliary distribution q(u) is treated as a black box. Quite an interesting read and proposal!

intractable likelihoods (even) for Alan

Posted in Kids, pictures, Statistics with tags , , , , , , , , , , , , on November 19, 2015 by xi'an

In connection with the official launch of the Alan Turing Institute (or ATI, of which Warwick is a partner), it funded an ATI Scoping workshop yesterday a week ago in Warwick around the notion(s) of intractable likelihood(s) and how this could/should fit within the themes of the Institute [hence the scoping]. This is one among many such scoping workshops taking place at all partners, as reported on the ATI website. Workshop that was quite relaxed and great fun, if only for getting together with most people (and friends) in the UK interested in the topic. But also pointing out some new themes I had not previously though of as related to ilike. For instance, questioning the relevance of likelihood for inference and putting forward decision theory under model misspecification, connecting with privacy and ethics [hence making intractable “good”!], introducing uncertain likelihood, getting more into network models, RKHS as a natural summary statistic, swarm of solutions for consensus inference… (And thanks to Mark Girolami for this homage to the iconic LP of the Sex Pistols!, that I played maniacally all over 1978…) My own two-cents into the discussion were mostly variations of other discussions, borrowing from ABC (and ABC slides) to call for a novel approach to approximate inference: