Alexandros Beskos

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Ajay JasraProfessor of Applied Mathematics, 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
Paul FearnheadProfessor of Statistics; Lancaster UniversityVerified email at lancs.ac.uk
JM Sanz-SernaUniversidad Carlos III de MadridVerified email at math.uc3m.es
Natesh S. PillaiHarvard UniversityVerified email at fas.harvard.edu
Alexandre ThieryAssociate Professor, National University of Singapore (NUS)Verified email at nus.edu.sg
Maria De IorioProfessor of Biostatistics, National University of Singapore & University College LondonVerified email at nus.edu.sg
Kody J. H. LawDepartment of Mathematics, University of ManchesterVerified email at manchester.ac.uk
Jochen VossLecturer in Statistics, University of LeedsVerified email at leeds.ac.uk
Nick WhiteleyUniversity of BristolVerified email at bristol.ac.uk
Frank J. PinskiUniversity of CincinnatiVerified email at ucmail.uc.edu
Mark GirolamiUniversity of CambridgeVerified email at cam.ac.uk
Shiwei LanASUVerified email at asu.edu
Patrick FarrellAssociate Professor of Mathematics, University of OxfordVerified email at maths.ox.ac.uk
Raul TemponeProfessor of Applied Mathematics, Director - Center for Uncertainty Quantification, KAUSTVerified email at kaust.edu.sa
Hamza RuzayqatPostdoctoral Research Fellow, King Abdullah University of Science and TechnologyVerified email at kaust.edu.sa

Alexandros Beskos

Reader 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	453	2006
Exact simulation of diffusions A Beskos, GO Roberts The Annals of Applied Probability 15 (4), 2422-2444, 2005	326	2005
Optimal tuning of the hybrid Monte Carlo algorithm A Beskos, N Pillai, G Roberts, JM Sanz-Serna, A Stuart Bernoulli 19 (5A), 1501-1534, 2013	311	2013
Retrospective exact simulation of diffusion sample paths with applications A Beskos, O Papaspiliopoulos, GO Roberts Bernoulli 12 (6), 1077-1098, 2006	264	2006
MCMC methods for diffusion bridges A Beskos, G Roberts, A Stuart, J Voss Stochastics and Dynamics 8 (03), 319-350, 2008	224	2008
On the stability of sequential Monte Carlo methods in high dimensions A Beskos, D Crisan, A Jasra The Annals of Applied Probability 24 (4), 1396-1445, 2014	177	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	143	2011
Optimal scalings for local Metropolis–Hastings chains on nonproduct targets in high dimensions A Beskos, G Roberts, A Stuart The Annals of Applied Probability 19 (3), 863-898, 2009	121	2009
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	119	2017
A factorisation of diffusion measure and finite sample path constructions A Beskos, O Papaspiliopoulos, GO Roberts Methodology and Computing in Applied Probability 10 (1), 85-104, 2008	118	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	101	2014
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	99	2017
Monte Carlo maximum likelihood estimation for discretely observed diffusion processes A Beskos, O Papaspiliopoulos, G Roberts The Annals of Statistics 37 (1), 223-245, 2009	95	2009
On the convergence of adaptive sequential Monte Carlo methods A Beskos, A Jasra, N Kantas, A Thiery The Annals of Applied Probability 26 (2), 1111-1146, 2016	90	2016
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	87*	2017
Sequential Monte Carlo methods for Bayesian elliptic inverse problems A Beskos, A Jasra, EA Muzaffer, AM Stuart Statistics and Computing 25 (4), 727-737, 2015	70	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	61*	2014
MCMC methods for sampling function space A Beskos, A Stuart Invited Lectures, Sixth International Congress on Industrial and Applied …, 2009	61	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	39	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	37	2013

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