Anthony Lee

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Arnaud DoucetProfessor of Statistics, University of Oxford & Senior Research Scientist, Google DeepMindVerified email at stats.ox.ac.uk
Christophe AndrieuProfessor of Statistics, University of BristolVerified email at bristol.ac.uk
Nick WhiteleyUniversity of BristolVerified email at bristol.ac.uk
Christopher DrovandiProfessor of Statistics, Queensland University of TechnologyVerified email at qut.edu.au
Chris HolmesVerified email at stats.ox.ac.uk
Christopher YauUniversity of OxfordVerified email at wrh.ox.ac.uk
Lawrence MurrayUber AIVerified email at uber.com
Pierre E. JacobESSEC Business SchoolVerified email at essec.edu
Matti ViholaDepartment of Mathematics and Statistics, University of JyväskyläVerified email at jyu.fi
Ajay JasraProfessor of Applied Mathematics & Statistics, KAUSTVerified email at kaust.edu.sa
Michael B. GilesProfessor of Scientific Computing, University of OxfordVerified email at maths.ox.ac.uk
Christian RobertUniversité Paris Dauphine, PSL & University of WarwickVerified email at ceremade.dauphine.fr
Adam M. JohansenUniversity of WarwickVerified email at warwick.ac.uk
David S. LeslieProfessor of Statistical Learning, Lancaster UniversityVerified email at lancaster.ac.uk
Sumeetpal Sidhu SinghTibra Foundation Chair in Mathematical Sciences, School of Mathematics, University of WollongongVerified email at uow.edu.au
Krzysztof LatuszynskiUniversity of Warwick, Department of StatisticsVerified email at warwick.ac.uk
David NottAssociate Professor of Statistics, National University of SingaporeVerified email at nus.edu.sg
François CaronUniversity of OxfordVerified email at stats.ox.ac.uk
Chris SherlockLancaster UniversityVerified email at lancaster.ac.uk
Clara GrazianUniversity of SydneyVerified email at sydney.edu.au

Anthony Lee

School of Mathematics, University of Bristol

Verified email at bristol.ac.uk - Homepage

Computational Statistics Sequential Monte Carlo Markov chain Monte Carlo Bayesian Inference


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On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods A Lee, C Yau, MB Giles, A Doucet, CC Holmes Journal of Computational and Graphical Statistics 19 (4), 769-789, 2010	372	2010
Optimistic Bayesian Sampling in Contextual-Bandit Problems BC May, N Korda, A Lee, DS Leslie Journal of Machine Learning Research 13, 2069-2106, 2012	217	2012
Bayesian synthetic likelihood LF Price, CC Drovandi, A Lee, DJ Nott Journal of Computational and Graphical Statistics 27 (1), 1-11, 2018	178	2018
Parallel resampling in the particle filter LM Murray, A Lee, PE Jacob Journal of Computational and Graphical Statistics 25 (3), 789-805, 2016	175	2016
The iterated auxiliary particle filter P Guarniero, AM Johansen, A Lee Journal of the American Statistical Association 112 (520), 1636-1647, 2017	100	2017
Bayesian indirect inference using a parametric auxiliary model CC Drovandi, AN Pettitt, A Lee	97	2015
Uniform ergodicity of the iterated conditional SMC and geometric ergodicity of particle Gibbs samplers C Andrieu, A Lee, M Vihola	89*	2018
On the role of interaction in sequential Monte Carlo algorithms N Whiteley, A Lee, K Heine	80	2016
Variance bounding and geometric ergodicity of Markov chain Monte Carlo kernels for approximate Bayesian computation A Lee, K Latuszynski Biometrika 101 (3), 655--671, 2014	58	2014
Accelerating Metropolis-Hastings algorithms by delayed acceptance M Banterle, C Grazian, A Lee, CP Robert Foundations of Data Science 1 (2), 103-128, 2019	54*	2019
Variance estimation in the particle filter A Lee, N Whiteley Biometrika 105 (3), 609--625, 2018	54	2018
The alive particle filter and its use in particle Markov chain Monte Carlo PD Moral, A Jasra, A Lee, C Yau, X Zhang Stochastic Analysis and Applications 33 (6), 943-974, 2015	52*	2015
Twisted particle filters N Whiteley, A Lee	50	2014
Stability of noisy Metropolis–Hastings FJ Medina-Aguayo, A Lee, GO Roberts Statistics and Computing 26 (6), 1187-1211, 2016	46	2016
A hierarchical bayesian framework for constructing sparsity-inducing priors A Lee, F Caron, A Doucet, C Holmes Arxiv preprint arXiv:1009.1914, 2010	42	2010
Global consensus Monte Carlo LJ Rendell, AM Johansen, A Lee, N Whiteley Journal of Computational and Graphical Statistics 30 (2), 249-259, 2020	37	2020
Forest resampling for distributed sequential Monte Carlo A Lee, N Whiteley Statistical Analysis and Data Mining: The ASA Data Science Journal 9 (4 …, 2016	32	2016
On the choice of MCMC kernels for approximate Bayesian computation with SMC samplers A Lee Proceedings of the 2012 Winter simulation conference (WSC), 1-12, 2012	32	2012
Pseudo-marginal Metropolis–Hastings sampling using averages of unbiased estimators C Sherlock, AH Thiery, A Lee Biometrika 104 (3), 727-734, 2017	31	2017
Sequential Monte Carlo methods A Doucet, A Lee Handbook of graphical models, 165-188, 2018	30	2018

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