Publications

(2020). Digital Health Management During and Beyond the COVID-19 Pandemic: Opportunities, Barriers, and Recommendations. JMIR Ment Health.

(2020). A Recommendation and Risk Classification System for Connecting Rough Sleepers to Essential Outreach Services.

(2020). coexist.

(2020). Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations. Statistics.

(2020). Diabetes and COVID-19 Related Mortality in the Critical Care Setting: A Real-Time National Cohort Study in England. Available at SSRN.

(2020). A geotemporal survey of hospital bed saturation across England during the first wave of the COVID-19 Pandemic. medRxiv.

(2019). Measuring sample quality with diffusions. Ann. Appl. Probab..

(2019). Design choices for productive, secure, data-intensive research at scale in the cloud.

(2018). Unbiased Monte Carlo: Posterior estimation for intractable/infinite-dimensional models. Bernoulli.

(2018). The Bouncy Particle Sampler: A Nonreversible Rejection-Free Markov Chain Monte Carlo Method. J. Am. Stat. Assoc..

(2018). Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains. Stat. Probab. Lett..

(2017). Multilevel Monte Carlo for Reliability Theory. Reliab. Eng. Syst. Saf..

(2017). The true cost of stochastic gradient Langevin dynamics. arXiv preprint arXiv.

(2017). Relativistic monte carlo. Artif. Intell..

(2017). Note on A. Barbour's paper on Stein's method for diffusion approximations. Electron. Commun. Probab..

(2017). Distributed Bayesian learning with stochastic natural gradient expectation propagation and the posterior server. J. Mach. Learn. Res..

(2017). An iterative technique for bounding derivatives of solutions of Stein equations. Electron. J. Probab..

(2017). An iterative technique for bounding derivatives of solutions of Stein equations. Electron. J. Probab..

(2016). Exploration of the (non-)asymptotic bias and variance of stochastic gradient langevin dynamics. J. Mach. Learn. Res..

(2016). Consistency and fluctuations for stochastic gradient Langevin dynamics. J. Mach. Learn. Res..

(2016). Consistency and fluctuations for stochastic gradient Langevin dynamics. J. Mach. Learn. Res..

(2015). Dimension-Independent MCMC Sampling for Inverse Problems with Non-Gaussian Priors. SIAM/ASA J. Uncertainty Quantification.

(2014). Spectral gaps for a Metropolis--Hastings algorithm in infinite dimensions. The Annals of Applied.

(2014). Bayesian inference with big data: a snapshot from a workshop. pdfs.semanticscholar.org.