Publications

Google Scholar - All updated publications

Becky Inkster, Ross O'Brien, Emma Selby, Smriti Joshi, Vinod Subramanian, Madhura Kadaba, Knut Schroeder, Suzi Godson, Kerstyn Comley, Sebastian Vollmer, Bilal a Mateen (2020). Digital Health Management During and Beyond the COVID-19 Pandemic: Opportunities, Barriers, and Recommendations. JMIR Ment Health.

Harrison Wilde, Lucia Lushi Chen, Austin Nguyen, Zoe Kimpel, Joshua Sidgwick, Adolfo De Unanue, Davide Veronese, Bilal Mateen, Rayid Ghani, Sebastian Vollmer (2020). A Recommendation and Risk Classification System for Connecting Rough Sleepers to Essential Outreach Services.

(2020). Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness. BMJ.

Gergo, Gaurav Venkataraman, Harrison Wild, Sebastian J. Vollmer Bohner (2020). coexist.

M B Giles, M B Majka, L Szpruch, S J Vollmer, Others (2020). Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations. Statistics.

J M Dennis, B a Mateen, R Sonabend, Others (2020). Diabetes and COVID-19 Related Mortality in the Critical Care Setting: A Real-Time National Cohort Study in England. Available at SSRN.

Bilal a Mateen, Harrison Wilde, John M Dennis, Andrew Duncan, Nicholas John Meyrick Thomas, Andrew P McGovern, Spiros Denaxas, Matt J Keeling, Sebastian Vollmer (2020). A geotemporal survey of hospital bed saturation across England during the first wave of the COVID-19 Pandemic. medRxiv.

Jackson Gorham, Andrew B Duncan, Sebastian Vollmer, Lester Mackey (2019). Measuring sample quality with diffusions. Ann. Appl. Probab..

Sergios Agapiou, Gareth O Roberts, Sebastian Vollmer (2018). Unbiased Monte Carlo: Posterior estimation for intractable/infinite-dimensional models. Bernoulli.

Alexandre Bouchard-Côté, Sebastian Vollmer, Arnaud Doucet (2018). The Bouncy Particle Sampler: A Nonreversible Rejection-Free Markov Chain Monte Carlo Method. J. Am. Stat. Assoc..

J Bierkens, A Bouchard-Côté, A Doucet, Others (2018). Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains. Stat. Probab. Lett..

Louis J M Aslett, Tigran Nagapetyan, Sebastian Vollmer (2017). Multilevel Monte Carlo for Reliability Theory. Reliab. Eng. Syst. Saf..

T Nagapetyan, A B Duncan, L Hasenclever, Others (2017). The true cost of stochastic gradient Langevin dynamics. arXiv preprint arXiv.

X Lu, V Perrone, L Hasenclever, Others (2017). Relativistic monte carlo. Artif. Intell..

Mikołaj J Kasprzak, Andrew B Duncan, Sebastian Vollmer, Others (2017). Note on A. Barbour's paper on Stein's method for diffusion approximations. Electron. Commun. Probab..

Leonard Hasenclever, Stefan Webb, Thibaut Lienart, Sebastian Vollmer, Balaji Lakshminarayanan, Charles Blundell, Yee Whye Teh (2017). Distributed Bayesian learning with stochastic natural gradient expectation propagation and the posterior server. J. Mach. Learn. Res..

Christian Döbler, Robert E Gaunt, Sebastian Vollmer, Others (2017). An iterative technique for bounding derivatives of solutions of Stein equations. Electron. J. Probab..

Christian Döbler, Robert E Gaunt, Sebastian Vollmer (2017). An iterative technique for bounding derivatives of solutions of Stein equations. Electron. J. Probab..

Sebastian Vollmer, Konstantinos C Zygalakis, Yee Whye Teh (2016). Exploration of the (non-)asymptotic bias and variance of stochastic gradient langevin dynamics. J. Mach. Learn. Res..

Yee Whye Teh, Alexandre H Thiery, Sebastian Vollmer (2016). Consistency and fluctuations for stochastic gradient Langevin dynamics. J. Mach. Learn. Res..

Yee Whye Teh, Alexandre H Thiery, Sebastian Vollmer (2016). Consistency and fluctuations for stochastic gradient Langevin dynamics. J. Mach. Learn. Res..

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

M Hairer, A M Stuart, S J Vollmer (2014). Spectral gaps for a Metropolis--Hastings algorithm in infinite dimensions. The Annals of Applied.

M Welling, Y W Teh, C Andrieu, J Kominiarczuk, Others (2014). Bayesian inference with big data: a snapshot from a workshop. pdfs.semanticscholar.org.

S J Vollmer (2013). Posterior consistency for Bayesian inverse problems through stability and regression results. Inverse Probl..

Sebastian Vollmer (2013). Efficient MCMC and Posterior Consistency for Bayesian Inverse Problems.