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
1672016
Consistency and fluctuations for stochastic gradient Langevin dynamics
YW Teh, AH Thiery, SJ Vollmer
Journal of Machine Learning Research 17, 2016
1672016
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
1482018
Spectral gaps for a Metropolis–Hastings algorithm in infinite dimensions
M Hairer, AM Stuart, SJ Vollmer
Annals of Applied Probability 24 (6), 2455-2490, 2014
1362014
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
682016
Measuring sample quality with diffusions
J Gorham, AB Duncan, SJ Vollmer, L Mackey
Annals of Applied Probability 29 (5), 2884-2928, 2019
652019
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
56*2017
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
472020
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
452021
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
402018
The true cost of stochastic gradient Langevin dynamics
T Nagapetyan, AB Duncan, L Hasenclever, SJ Vollmer, L Szpruch, ...
arXiv preprint arXiv:1706.02692, 2017
392017
Posterior consistency for Bayesian inverse problems through stability and regression results
SJ Vollmer
Inverse Problems 29 (12), 125011, 2013
382013
Relativistic monte carlo
X Lu, V Perrone, L Hasenclever, YW Teh, S Vollmer
Artificial Intelligence and Statistics, 1236-1245, 2017
342017
An iterative technique for bounding derivatives of solutions of Stein equations
C Döbler, RE Gaunt, SJ Vollmer
Electronic Journal of Probability 22, 2017
322017
Multilevel Monte Carlo for reliability theory
LJM Aslett, T Nagapetyan, SJ Vollmer
Reliability Engineering & System Safety 165, 188-196, 2017
282017
(Non-) asymptotic properties of stochastic gradient Langevin dynamics
SJ Vollmer, KC Zygalakis
arXiv preprint arXiv:1501.00438, 2015
272015
Reporting guidelines for clinical trials evaluating artificial intelligence interventions are needed
X Liu, SC Rivera, L Faes, LF Di Ruffano, C Yau, PA Keane10, ...
Nat. Med 25, 1467-1468, 2019
202019
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
182018
Dimension-independent MCMC sampling for inverse problems with non-Gaussian priors
SJ Vollmer
SIAM/ASA Journal on Uncertainty Quantification 3 (1), 535-561, 2015
182015
Dimension-independent MCMC sampling for inverse problems with non-Gaussian priors
SJ Vollmer
SIAM/ASA Journal on Uncertainty Quantification 3 (1), 535-561, 2015
182015
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