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
The Journal of Machine Learning Research 17 (1), 193-225, 2016
1492016
Consistency and fluctuations for stochastic gradient Langevin dynamics
YW Teh, AH Thiery, SJ Vollmer
The Journal of Machine Learning Research 17 (1), 193-225, 2016
1492016
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
1172018
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
1162014
Measuring sample quality with kernels
J Gorham, L Mackey
arXiv preprint arXiv:1703.01717, 2017
102*2017
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
562016
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
49*2017
Posterior consistency for Bayesian inverse problems through stability and regression results
SJ Vollmer
Inverse Problems 29 (12), 125011, 2013
372013
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
342018
The true cost of stochastic gradient Langevin dynamics
T Nagapetyan, AB Duncan, L Hasenclever, SJ Vollmer, L Szpruch, ...
arXiv preprint arXiv:1706.02692, 2017
322017
An iterative technique for bounding derivatives of solutions of Stein equations
C Döbler, RE Gaunt, SJ Vollmer
Electronic Journal of Probability 22, 2017
292017
Relativistic monte carlo
X Lu, V Perrone, L Hasenclever, YW Teh, S Vollmer
Artificial Intelligence and Statistics, 1236-1245, 2017
282017
Multilevel Monte Carlo for reliability theory
LJM Aslett, T Nagapetyan, SJ Vollmer
Reliability Engineering & System Safety 165, 188-196, 2017
242017
(Non-) asymptotic properties of stochastic gradient Langevin dynamics
SJ Vollmer, KC Zygalakis
arXiv preprint arXiv:1501.00438, 2015
242015
Dimension-independent MCMC sampling for inverse problems with non-Gaussian priors
SJ Vollmer
SIAM/ASA Journal on Uncertainty Quantification 3 (1), 535-561, 2015
172015
Dimension-independent MCMC sampling for inverse problems with non-Gaussian priors
SJ Vollmer
SIAM/ASA Journal on Uncertainty Quantification 3 (1), 535-561, 2015
172015
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
162018
Unbiased Monte Carlo: Posterior estimation for intractable/infinite-dimensional models
S Agapiou, GO Roberts, SJ Vollmer
Bernoulli 24 (3), 1726-1786, 2018
13*2018
Multilevel monte carlo for scalable bayesian computations
M Giles, T Nagapetyan, L Szpruch, S Vollmer, K Zygalakis
arXiv preprint arXiv:1609.06144, 2016
112016
Note on A. Barbour’s paper on Stein’s method for diffusion approximations
MJ Kasprzak, AB Duncan, SJ Vollmer
Electronic Communications in Probability 22, 2017
102017
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