Articoli con mandati relativi all'accesso pubblico - Alexandros BeskosUlteriori informazioni
Disponibili pubblicamente: 27
Optimal tuning of the hybrid Monte Carlo algorithm
A Beskos, N Pillai, G Roberts, JM Sanz-Serna, A Stuart
Mandati: UK Engineering and Physical Sciences Research Council, Government of Spain
On the stability of sequential Monte Carlo methods in high dimensions
A Beskos, D Crisan, A Jasra
Mandati: UK Engineering and Physical Sciences Research Council
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
Mandati: US Department of Defense, UK Engineering and Physical Sciences Research …
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
Mandati: US Department of Energy
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
Mandati: UK Engineering and Physical Sciences Research Council
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
Mandati: UK Engineering and Physical Sciences Research Council
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
Mandati: US Department of Energy
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
Mandati: UK Engineering and Physical Sciences Research Council, Government of Spain
Advanced MCMC methods for sampling on diffusion pathspace
A Beskos, K Kalogeropoulos, E Pazos
Stochastic Processes and their Applications 123 (4), 1415-1453, 2013
Mandati: UK Engineering and Physical Sciences Research Council
Particle filtering for stochastic Navier--Stokes signal observed with linear additive noise
FP Llopis, N Kantas, A Beskos, A Jasra
SIAM Journal on Scientific Computing 40 (3), A1544-A1565, 2018
Mandati: UK Engineering and Physical Sciences Research Council
Bayesian inference for partially observed stochastic differential equations driven by fractional Brownian motion
A Beskos, J Dureau, K Kalogeropoulos
Biometrika 102 (4), 809-827, 2015
Mandati: UK Engineering and Physical Sciences Research Council
Asymptotic analysis of the random-walk Metropolis algorithm on ridged densities
A Beskos, G Roberts, A Thiery, N Pillai
Annals of Applied Probability 28 (5), 2966-3001, 2018
Mandati: US Department of Defense
A Lagged Particle Filter for Stable Filtering of certain High-Dimensional State-Space Models
H Ruzayqat, A Er-Raiy, A Beskos, D Crisan, A Jasra, N Kantas
SIAM/ASA Journal on Uncertainty Quantification 10 (3), 1130-1161, 2022
Mandati: European Commission
Bridging trees for posterior inference on ancestral recombination graphs
K Heine, A Beskos, A Jasra, D Balding, M De Iorio
Proceedings of the Royal Society A 474 (2220), 20180568, 2018
Mandati: UK Engineering and Physical Sciences Research Council
Efficient sequential Monte Carlo algorithms for integrated population models
A Finke, R King, A Beskos, P Dellaportas
Journal of Agricultural, Biological and Environmental Statistics 24, 204-224, 2019
Mandati: UK Engineering and Physical Sciences Research Council
Bayesian inference for duplication–mutation with complementarity network models
A Jasra, A Persing, A Beskos, K Heine, M De Iorio
Journal of Computational Biology 22 (11), 1025-1033, 2015
Mandati: UK Engineering and Physical Sciences Research Council
Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo
W van den Boom, A Jasra, MD Iorio, A Beskos, JG Eriksson
Statistics and Computing 32, article no 36, 1-19, 2022
Mandati: A*Star, Singapore, National Medical Research Council, Singapore, National …
Parameter Estimation with Increased Precision for Elliptic and Hypo-elliptic Diffusions
Y Iguchi, A Beskos, MM Graham
Bernoulli 31 (1), 333-358, 2025
Mandati: UK Engineering and Physical Sciences Research Council
A 4D-Var method with flow-dependent background covariances for the shallow-water equations
D Paulin, A Jasra, A Beskos, D Crisan
Statistics and Computing 32, article no 65, 1-15, 2022
Mandati: US Department of Defense, UK Engineering and Physical Sciences Research Council
On concentration properties of partially observed chaotic systems
D Paulin, A Jasra, D Crisan, A Beskos
Advances in Applied Probability 50 (2), 440-479, 2018
Mandati: UK Engineering and Physical Sciences Research Council
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