Alexandros Beskos

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Ajay JasraProfessor of Data Science, The Chinese University of Hong Kong, ShenzhenVerified email at cuhk.edu.cn
Gareth RobertsProfessor of Statistics, University of WarwickVerified email at warwick.ac.uk
Andrew M StuartComputing + Mathematical Sciences, CaltechVerified email at caltech.edu
Dan CrisanProfessor of Mathematics, Imperial College LondonVerified email at imperial.ac.uk
Omiros PapaspiliopoulosBocconiVerified email at unibocconi.it
Nikolas KantasDept. of Mathematics, Imperial College LondonVerified email at imperial.ac.uk
JM Sanz-SernaUniversidad Carlos III de MadridVerified email at math.uc3m.es
Maria De IorioProfessor of Biostatistics, National University of SingaporeVerified email at nus.edu.sg
Natesh S. PillaiHarvard UniversityVerified email at fas.harvard.edu
Paul FearnheadProfessor of Statistics; Lancaster UniversityVerified email at lancs.ac.uk
Alexandre ThieryAssociate Professor, National University of Singapore (NUS)Verified email at nus.edu.sg
Matthew M. GrahamResearch data scientist, University College LondonVerified email at ucl.ac.uk
Willem van den BoomScientist, Agency for Science Technology and ResearchVerified email at sics.a-star.edu.sg
Kody J. H. LawProfessor at the University of Manchester and AI Research Scientist at MetaVerified email at meta.com
Hamza RuzayqatResearch Scientist, King Abdullah University of Science and TechnologyVerified email at kaust.edu.sa
Konstantinos KalogeropoulosAssociate Professor of Statistics, London School of EconomicsVerified email at lse.ac.uk
Jochen VossLecturer in Statistics, University of LeedsVerified email at leeds.ac.uk
Mark GirolamiUniversity of CambridgeVerified email at cam.ac.uk
Shiwei LanASUVerified email at asu.edu
Patrick FarrellProfessor, University of OxfordVerified email at maths.ox.ac.uk

Alexandros Beskos

Professor in Statistics, UCL

Verified email at ucl.ac.uk - Homepage

Bayesian Statistics Computational Statistics Statistical Modelling Financial Statistics Biostatistics


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Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion) A Beskos, O Papaspiliopoulos, GO Roberts, P Fearnhead Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2006	498	2006
Optimal tuning of the hybrid Monte Carlo algorithm A Beskos, N Pillai, G Roberts, JM Sanz-Serna, A Stuart	395	2013
Exact simulation of diffusions A Beskos, GO Roberts	375	2005
Retrospective exact simulation of diffusion sample paths with applications A Beskos, O Papaspiliopoulos, GO Roberts Bernoulli 12 (6), 1077-1098, 2006	302	2006
MCMC methods for diffusion bridges A Beskos, G Roberts, A Stuart, J Voss Stochastics and Dynamics 8 (03), 319-350, 2008	259	2008
On the stability of sequential Monte Carlo methods in high dimensions A Beskos, D Crisan, A Jasra	206	2014
Geometric MCMC for infinite-dimensional inverse problems A Beskos, M Girolami, S Lan, PE Farrell, AM Stuart Journal of Computational Physics 335, 327-351, 2017	167	2017
Hybrid monte carlo on hilbert spaces A Beskos, FJ Pinski, JM Sanz-Serna, AM Stuart Stochastic Processes and their Applications 121 (10), 2201-2230, 2011	166	2011
Optimal scalings for local Metropolis–Hastings chains on nonproduct targets in high dimensions A Beskos, G Roberts, A Stuart	142	2009
A factorisation of diffusion measure and finite sample path constructions A Beskos, O Papaspiliopoulos, GO Roberts Methodology and Computing in Applied Probability 10, 85-104, 2008	133	2008
Sequential Monte Carlo methods for high-dimensional inverse problems: A case study for the Navier--Stokes equations N Kantas, A Beskos, A Jasra SIAM/ASA Journal on Uncertainty Quantification 2 (1), 464-489, 2014	130	2014
A stable particle filter for a class of high-dimensional state-space models A Beskos, D Crisan, A Jasra, K Kamatani, Y Zhou Advances in Applied Probability 49 (1), 24-48, 2017	127*	2017
Multilevel sequential monte carlo samplers A Beskos, A Jasra, K Law, R Tempone, Y Zhou Stochastic Processes and their Applications 127 (5), 1417-1440, 2017	124	2017
On the convergence of adaptive sequential Monte Carlo methods A Beskos, A Jasra, N Kantas, A Thiery	117	2016
Monte Carlo maximum likelihood estimation for discretely observed diffusion processes A Beskos, O Papaspiliopoulos, G Roberts	116	2009
Sequential Monte Carlo methods for Bayesian elliptic inverse problems A Beskos, A Jasra, EA Muzaffer, AM Stuart Statistics and Computing 25, 727-737, 2015	81	2015
Error bounds and normalising constants for sequential Monte Carlo samplers in high dimensions A Beskos, DO Crisan, A Jasra, N Whiteley Advances in Applied Probability 46 (1), 279-306, 2014	66*	2014
MCMC methods for sampling function space A Beskos, A Stuart Invited Lectures, Sixth International Congress on Industrial and Applied …, 2009	64	2009
Multilevel sequential Monte Carlo with dimension-independent likelihood-informed proposals A Beskos, A Jasra, K Law, Y Marzouk, Y Zhou SIAM/ASA Journal on Uncertainty Quantification 6 (2), 762-786, 2018	49	2018
Markov chain Monte Carlo for exact inference for diffusions G Sermaidis, O Papaspiliopoulos, GO Roberts, A Beskos, P Fearnhead Scandinavian Journal of Statistics 40 (2), 294-321, 2013	47	2013

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