Browse by UCL people
Group by: Type | Date
Number of items: 49.
2024
Beskos, Alexandros;
Guillas, Serge;
Giles, Daniel;
Graham, Matthew;
Giordano, Mosè;
Koskela, Tuomas;
(2024)
ParticleDA.jl v.1.0: A real-time data assimilation software platform.
Geoscientific Model Development Discussions
10.5194/gmd-2023-38.
(In press).
|
Ruzayqat, Hamza;
Beskos, Alexandros;
Crisan, Dan;
Jasra, Ajay;
Kantas, Nikolas;
(2024)
Sequential Markov Chain Monte Carlo for Lagrangian Data Assimilation with Applications to Unknown Data Locations.
Quarterly Journal of the Royal Meteorological Society
(In press).
|
2023
Franzolini, Beatrice;
Beskos, Alexandros;
De Iorio, Maria;
Koziell, Warrick Poklewski;
Grzeszkiewicz, Karolina;
(2023)
Change point detection in dynamic Gaussian graphical models: the impact of COVID-19 pandemic on the US stock market.
The Annals of Applied Statistics
(In press).
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Ruzayqat, Hamza;
Beskos, Alexandros;
Crisan, Dan;
Jasra, Ajay;
Kantas, Nikolas;
(2023)
Unbiased Estimation using a Class of Diffusion Processes.
Journal of Computational Physics
, 472
, Article 111643. 10.1016/j.jcp.2022.111643.
|
2022
Beskos, A;
Kamatani, K;
(2022)
MCMC Algorithms for Posteriors on Matrix Spaces.
Journal of Computational and Graphical Statistics
, 31
(3)
pp. 721-738.
10.1080/10618600.2022.2058953.
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Boom, Willem van den;
Beskos, Alexandros;
Iorio, Maria De;
(2022)
The G-Wishart Weighted Proposal Algorithm: Efficient Posterior Computation for Gaussian Graphical Models.
Journal of Computational and Graphical Statistics
, 31
(4)
pp. 1215-1224.
10.1080/10618600.2022.2050250.
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Boom, Willem van den;
De Iorio, Maria;
Beskos, Alexandros;
(2022)
Bayesian Learning of Graph Substructures.
Bayesian Analysis
10.1214/22-BA1338.
(In press).
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Boom, Willem van den;
Jasra, Ajay;
De Iorio, Maria;
Beskos, Alexandros;
Eriksson, Johan G;
(2022)
Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo.
Statistics and Computing
, 32
, Article 36. 10.1007/s11222-022-10093-3.
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Franzolini, Beatrice;
Beskos, Alexandros;
Iorio, Maria De;
Koziell, Warrick Poklewski;
Grzeszkiewicz, Karolina;
(2022)
Change point detection in dynamic Gaussian graphical models: the impact
of COVID-19 pandemic on the US stock market.
arXiv: Ithaca, NY, USA.
|
Graham, Matthew M.;
Thiery, Alexandre H.;
Beskos, Alexandros;
(2022)
Manifold Markov chain Monte Carlo methods for Bayesian inference in diffusion models.
Journal of the Royal Statistical Society: Series B (Statistical Methodology)
, 84
(4)
pp. 1229-1256.
10.1111/rssb.12497.
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Iguchi, Yuga;
Beskos, Alexandros;
Graham, Matthew M;
(2022)
Parameter Estimation with Increased Precision for Elliptic and Hypo-elliptic Diffusions.
arXiv: Ithaca, NY, USA.
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Paulin, Daniel;
Jasra, Ajay;
Beskos, Alexandros;
Crisan, Dan;
(2022)
A 4D-Var Method with Flow-Dependent Background Covariances for the Shallow-Water Equations.
Statistics and Computing
, 32
, Article 65. 0.1007/s11222-022-10119-w.
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Ruzayqat, Hamza;
Er-raiy, Aimad;
Beskos, Alexandros;
Crisan, Dan;
Jasra, Ajay;
Kantas, Nikolas;
(2022)
A Lagged Particle Filter for Stable Filtering of Certain High-Dimensional State-Space Models.
SIAM/ASA Journal on Uncertainty Quantification
, 10
(3)
pp. 1130-1161.
10.1137/21M1450392.
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Yonekura, S;
Beskos, A;
(2022)
Online Smoothing for Diffusion Processes Observed with Noise.
Journal of Computational and Graphical Statistics
, 31
(4)
pp. 1344-1360.
10.1080/10618600.2022.2027243.
|
2021
Beskos, A;
Crisan, D;
Jasra, A;
Kantas, N;
Ruzayqat, HM;
(2021)
Score-Based Parameter Estimation for a Class of Continuous-Time State Space Models.
SIAM Journal on Scientific Computing
(In press).
|
Yonekura, S;
Beskos, A;
Singh, SS;
(2021)
Asymptotic analysis of model selection criteria for general hidden Markov models.
Stochastic Processes and their Applications
, 132
pp. 164-191.
10.1016/j.spa.2020.10.006.
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2020
Ye, L;
Beskos, A;
Iorio, MD;
Hao, J;
(2020)
Monte Carlo Co-Ordinate Ascent Variational Inference.
Statistics and Computing
10.1007/s11222-020-09924-y.
(In press).
|
2019
Finke, A;
King, R;
Beskos, A;
Dellaportas, P;
(2019)
Efficient Sequential Monte Carlo Algorithms for Integrated Population Models.
Journal of Agricultural, Biological and Environmental Statistics
, 24
(2)
pp. 204-224.
10.1007/s13253-018-00349-9.
|
2018
Beskos, A;
Jasra, A;
Law, K;
Marzouk, Y;
Zhou, Y;
(2018)
Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals.
SIAM-ASA Journal on Uncertainty Quantification
, 6
(2)
pp. 762-786.
10.1137/17M1120993.
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Beskos, A;
Roberts, G;
Thiery, A;
Pillai, N;
(2018)
Asymptotic Analysis of the Random-walk Metropolis Algorithm on Ridged Densities.
Annals of Applied Probability
, 28
(5)
pp. 2966-3001.
10.1214/18-AAP1380.
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Heine, K;
Beskos, A;
Jasra, A;
Balding, D;
De Iorio, M;
(2018)
Bridging trees for posterior inference on ancestral recombination graphs.
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
, 474
(2220)
, Article 20180568. 10.1098/rspa.2018.0568.
|
Llopis, FP;
Kantas, N;
Beskos, A;
Jasra, A;
(2018)
Particle Filtering for Stochastic Navier–Stokes Observed with Linear Additive Noise.
SIAM Journal on Scientific Computing
, 40
(3)
A1544-A1565.
10.1137/17M1151900.
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Paulin, D;
Jasra, A;
Crisan, D;
Beskos, A;
(2018)
On concentration properties of partially observed chaotic systems.
Advances in Applied Probability
, 50
(2)
pp. 440-479.
10.1017/apr.2018.21.
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Paulin, D;
Jasra, A;
Crisan, D;
Beskos, A;
(2018)
Optimization Based Methods for Partially Observed Chaotic Systems.
Foundations of Computational Mathematics
10.1007/s10208-018-9388-x.
(In press).
|
2017
Beskos, A;
Crisan, D;
Jasra, A;
Kamatani, K;
Zhou, Y;
(2017)
A stable particle filter for a class of high-dimensional state-space models.
Advances in Applied Probability
, 49
(1)
pp. 24-48.
10.1017/apr.2016.77.
|
Beskos, A;
Girolami, M;
Lan, S;
Farrell, PE;
Stuart, AM;
(2017)
Geometric MCMC for infinite-dimensional inverse problems.
Journal of Computational Physics
, 335
pp. 327-351.
10.1016/j.jcp.2016.12.041.
|
Beskos, A;
Jasra, A;
Law, K;
Tempone, R;
Zhou, Y;
(2017)
Multilevel sequential Monte Carlo samplers.
Stochastic Processes and their Applications
, 127
(5)
pp. 1417-1440.
10.1016/j.spa.2016.08.004.
|
2016
Beskos, A;
Jasra, A;
Kantas, N;
Thiery, A;
(2016)
On the convergence of adaptive sequential Monte Carlo methods.
Annals of Applied Probability
, 26
(2)
pp. 1111-1146.
10.1214/15-AAP1113.
|
2015
Beskos, A;
Dureau, J;
Kalogeropoulos, K;
(2015)
Bayesian inference for partially observed stochastic differential equations driven by fractional Brownian motion.
Biometrika
, 102
(4)
pp. 809-827.
10.1093/biomet/asv051.
|
Beskos, A;
Jasra, A;
Muzaffer, EA;
Stuart, AM;
(2015)
Sequential Monte Carlo methods for Bayesian elliptic inverse problems.
Statistics and Computing
, 25
(4)
pp. 727-737.
10.1007/s11222-015-9556-7.
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Jasra, A;
Persing, A;
Beskos, A;
Heine, K;
De Iorio, M;
(2015)
Bayesian inference for duplication-mutation with complementarity network models.
Journal of Computational Biology
, 22
(11)
pp. 1025-1033.
10.1089/cmb.2015.0072.
|
Persing, A;
Jasra, A;
Beskos, A;
Balding, D;
De Iorio, M;
(2015)
A Simulation Approach for Change-Points on Phylogenetic Trees.
Journal of Computational Biology
, 22
(1)
10.1089/cmb.2014.0218.
|
2014
Beskos, A;
(2014)
A stable manifold MCMC method for high dimensions.
Statistics and Probability Letters
, 90
(1)
pp. 46-52.
10.1016/j.spl.2014.03.016.
|
Beskos, A;
Crisan, D;
Jasra, A;
(2014)
On the Stability of Sequential Monte Carlo Methods in High Dimensions.
Annals of Applied Probability
, 24
(4)
pp. 1396-1445.
10.1214/13-AAP951.
|
Beskos, A;
Crisan, DO;
Jasra, A;
Whiteley, N;
(2014)
Error bounds and normalising constants for sequential monte carlo samplers in high dimensions.
Advances in Applied Probability
, 46
(1)
pp. 279-306.
10.1239/aap/1396360114.
|
Guo, X;
Beskos, A;
Siddiqui, A;
(2014)
The natural hedge of a gas-fired power plant.
Computational Management Science
, 13
(1)
pp. 63-86.
10.1007/s10287-014-0222-x.
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Kantas, N;
Beskos, A;
Jasra, A;
(2014)
Sequential Monte Carlo Methods for High-Dimensional Inverse Problems: A case study for the Navier-Stokes equations.
SIAM/ASA Journal on Uncertainty Quantification
, 2
(1)
pp. 464-489.
10.1137/130930364.
|
2013
Beskos, A;
Kalogeropoulos, K;
Pazos, E;
(2013)
Advanced MCMC methods for sampling on diffusion pathspace.
Stochastic Processes and their Applications
, 123
(4)
pp. 1415-1453.
10.1016/j.spa.2012.12.001.
|
Beskos, A;
Pillai, N;
Roberts, G;
Sanz-Serna, J-M;
Stuart, A;
(2013)
Optimal tuning of the hybrid Monte Carlo algorithm.
Bernoulli
, 19
(5A)
pp. 1501-1534.
10.3150/12-BEJ414.
|
Sermaidis, G;
Papaspiliopoulos, O;
Roberts, GO;
Beskos, A;
Fearnhead, P;
(2013)
Markov Chain Monte Carlo for Exact Inference for Diffusions.
Scandinavian Journal of Statistics
, 40
(2)
pp. 294-321.
10.1111/j.1467-9469.2012.00812.x.
|
2012
Beskos, A;
Peluchetti, S;
Roberts, G;
(2012)
epsilon-Strong simulation of the Brownian path.
Bernoulli
, 18
(4)
pp. 1223-1248.
10.3150/11-BEJ383.
|
2011
Beskos, A;
Pinski, FJ;
Sanz-Serna, JM;
Stuart, AM;
(2011)
Hybrid Monte Carlo on Hilbert spaces.
Stochastic Processes and their Applications
, 121
(10)
pp. 2201-2230.
10.1016/j.spa.2011.06.003.
|
2009
Beskos, A;
Papaspiliopoulos, O;
Roberts, G;
(2009)
Monte Carlo Maximum Likelihood Estimation for Discretely Observed Diffusion Processes.
The Annals of Statistics
, 37
(1)
223 - 245.
10.1214/07-AOS550.
|
Beskos, A;
Roberts, G;
Stuart, A;
(2009)
Optimal Scalings for Local Metropolis-hastings Chains on Nonproduct Targets in High Dimensions.
The Annals of Applied Probability
, 19
(3)
863 - 898.
10.1214/08-AAP563.
|
2008
Beskos, A;
Papaspiliopoulos, O;
Roberts, GO;
(2008)
A factorisation of diffusion measure and finite sample path constructions.
Methodology and Computing in Applied Probability
, 10
(1)
pp. 85-104.
10.1007/s11009-007-9060-4.
|
2006
Beskos, A;
Papaspiliopoulos, O;
Roberts, GO;
(2006)
Retrospective exact simulation of diffusion sample paths with applications.
Bernoulli
, 12
(6)
pp. 1077-1098.
10.3150/bj/1165269151.
|
Beskos, A;
Papaspiliopoulos, O;
Roberts, GO;
Fearnhead, P;
(2006)
Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion).
Journal of the Royal Statistical Society series B-statistical methodology
, 68
pp. 333-382.
10.1111/j.1467-9868.2006.00552.x.
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2005
Beskos, A;
Roberts, G;
(2005)
One-shot CFTP; Application to a class of truncated Gaussian densities.
Methodology and Computing in Applied Probability
, 7
pp. 407-437.
10.1007/s11009-005-5001-2.
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Beskos, A;
Roberts, GO;
(2005)
Exact simulation of diffusions.
The Annals of Applied Probability
, 15
(4)
2422 - 2444.
10.1214/105051605000000485.
|