Sebastian J. Vollmer
Sebastian J. Vollmer
University of Warwick/Turing
Verified email at turing.ac.uk - Homepage
Title
Cited by
Cited by
Year
Consistency and fluctuations for stochastic gradient Langevin dynamics
YW Teh, AH Thiery, SJ Vollmer
Journal of Machine Learning Research 17, 2016
1872016
Consistency and fluctuations for stochastic gradient Langevin dynamics
YW Teh, AH Thiery, SJ Vollmer
Journal of Machine Learning Research 17, 2016
1872016
The bouncy particle sampler: A nonreversible rejection-free Markov chain Monte Carlo method
A Bouchard-Côté, SJ Vollmer, A Doucet
Journal of the American Statistical Association 113 (522), 855-867, 2018
1692018
Spectral gaps for a Metropolis–Hastings algorithm in infinite dimensions
M Hairer, AM Stuart, SJ Vollmer
The Annals of Applied Probability 24 (6), 2455-2490, 2014
1452014
Improving survival of critical care patients with coronavirus disease 2019 in England: a national cohort study, March to June 2020
JM Dennis, AP McGovern, SJ Vollmer, BA Mateen
Critical care medicine 49 (2), 209, 2021
812021
Exploration of the (non-) asymptotic bias and variance of stochastic gradient Langevin dynamics
SJ Vollmer, KC Zygalakis, YW Teh
The Journal of Machine Learning Research 17 (1), 5504-5548, 2016
782016
Measuring sample quality with diffusions
J Gorham, AB Duncan, SJ Vollmer, L Mackey
The Annals of Applied Probability 29 (5), 2884-2928, 2019
732019
Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness
S Vollmer, BA Mateen, G Bohner, FJ Király, R Ghani, P Jonsson, ...
bmj 368, 2020
652020
Distributed Bayesian learning with stochastic natural gradient expectation propagation and the posterior server
L Hasenclever, S Webb, T Lienart, S Vollmer, B Lakshminarayanan, ...
The Journal of Machine Learning Research 18 (1), 3744-3780, 2017
59*2017
Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains
J Bierkens, A Bouchard-Côté, A Doucet, AB Duncan, P Fearnhead, ...
Statistics & Probability Letters 136, 148-154, 2018
432018
The true cost of stochastic gradient Langevin dynamics
T Nagapetyan, AB Duncan, L Hasenclever, SJ Vollmer, L Szpruch, ...
arXiv preprint arXiv:1706.02692, 2017
412017
Relativistic monte carlo
X Lu, V Perrone, L Hasenclever, YW Teh, S Vollmer
Artificial Intelligence and Statistics, 1236-1245, 2017
392017
Posterior consistency for Bayesian inverse problems through stability and regression results
SJ Vollmer
Inverse Problems 29 (12), 125011, 2013
392013
Multilevel Monte Carlo for reliability theory
LJM Aslett, T Nagapetyan, SJ Vollmer
Reliability Engineering & System Safety 165, 188-196, 2017
342017
An iterative technique for bounding derivatives of solutions of Stein equations
C Döbler, RE Gaunt, SJ Vollmer
Electronic Journal of Probability 22, 1-39, 2017
332017
Type 2 diabetes and COVID-19–Related mortality in the critical care setting: a national cohort study in England, March–July 2020
JM Dennis, BA Mateen, R Sonabend, NJ Thomas, KA Patel, AT Hattersley, ...
Diabetes care 44 (1), 50-57, 2021
322021
(Non-) asymptotic properties of stochastic gradient Langevin dynamics
SJ Vollmer, KC Zygalakis
arXiv preprint arXiv:1501.00438, 2015
292015
Reporting guidelines for clinical trials evaluating artificial intelligence interventions are needed
X Liu, SC Rivera, L Faes, LFD Ruffano, C Yau, PA Keane, H Ashrafian, ...
Nat Med 25 (10), 1467-1468, 2019
262019
Machine learning and AI research for patient benefit: 20 critical questions on transparency, replicability, ethics and effectiveness
S Vollmer, BA Mateen, G Bohner, FJ Király, R Ghani, P Jonsson, ...
arXiv preprint arXiv:1812.10404, 2018
232018
Dimension-independent MCMC sampling for inverse problems with non-Gaussian priors
SJ Vollmer
SIAM/ASA Journal on Uncertainty Quantification 3 (1), 535-561, 2015
202015
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