Alexandros Beskos

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Ajay JasraProfessor of Applied Mathematics & Statistics, KAUSTVerified email at kaust.edu.sa
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
Paul FearnheadProfessor of Statistics; Lancaster UniversityVerified email at lancs.ac.uk
Natesh S. PillaiHarvard UniversityVerified email at fas.harvard.edu
Maria De IorioProfessor of Biostatistics, National University of Singapore & University College LondonVerified email at nus.edu.sg
Alexandre ThieryAssociate Professor, National University of Singapore (NUS)Verified email at nus.edu.sg
Kody J. H. LawDepartment of Mathematics, University of ManchesterVerified email at manchester.ac.uk
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
Frank J. PinskiUniversity of CincinnatiVerified email at ucmail.uc.edu
Nick WhiteleyUniversity of BristolVerified email at bristol.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
Hamza RuzayqatResearch Scientist, King Abdullah University of Science and TechnologyVerified email at kaust.edu.sa

Alexandros Beskos

Professor in Statistics, UCL

Verified email at ucl.ac.uk - Homepage

Bayesian Statistics Financial Statistics Machine Learning Biostatistics Particle Filtering


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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	472	2006
Optimal tuning of the hybrid Monte Carlo algorithm A Beskos, N Pillai, G Roberts, JM Sanz-Serna, A Stuart	359	2013
Exact simulation of diffusions A Beskos, GO Roberts	347	2005
Retrospective exact simulation of diffusion sample paths with applications A Beskos, O Papaspiliopoulos, GO Roberts Bernoulli 12 (6), 1077-1098, 2006	284	2006
MCMC methods for diffusion bridges A Beskos, G Roberts, A Stuart, J Voss Stochastics and Dynamics 8 (03), 319-350, 2008	239	2008
On the stability of sequential Monte Carlo methods in high dimensions A Beskos, D Crisan, A Jasra	194	2014
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	155	2011
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	138	2017
Optimal scalings for local Metropolis–Hastings chains on nonproduct targets in high dimensions A Beskos, G Roberts, A Stuart	131	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	123	2008
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	115	2017
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	114	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	106*	2017
On the convergence of adaptive sequential Monte Carlo methods A Beskos, A Jasra, N Kantas, A Thiery	103	2016
Monte Carlo maximum likelihood estimation for discretely observed diffusion processes A Beskos, O Papaspiliopoulos, G Roberts	102	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	73	2015
MCMC methods for sampling function space A Beskos, A Stuart Invited Lectures, Sixth International Congress on Industrial and Applied …, 2009	66	2009
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	65*	2014
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	45	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	40	2013

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