Andrew Golightly

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Darren WilkinsonProfessor of Statistics, Durham University, U.K.Verified email at durham.ac.uk
Chris SherlockLancaster UniversityVerified email at lancaster.ac.uk
Richard BoysProfessor of Applied Statistics, Newcastle University, UKVerified email at ncl.ac.uk
Daniel A HendersonNewcastle University, UKVerified email at ncl.ac.uk
Colin S GillespieSenior Statistics Lecturer, Newcastle UniversityVerified email at newcastle.ac.uk
Andrew William BaggaleySchool of Mathematics and Statistics, Newcastle UniversityVerified email at ncl.ac.uk
Dennis PrangleUniversity of BristolVerified email at bristol.ac.uk
Tom RyderQualcommVerified email at qti.qualcomm.com
Graeme SarsonNewcastle UniversityVerified email at ncl.ac.uk
Anvar ShukurovProfessor of Astrophysical Fluid Dynamics, Newcastle University, UKVerified email at ncl.ac.uk
A.S.McGoughNewcastle UniversityVerified email at newcastle.ac.uk
Theodore KypraiosProfessor of Statistics, University of NottinghamVerified email at nottingham.ac.uk
Nick ParkerProfessor, School of Mathematics, Statistics & Physics, Newcastle UniversityVerified email at ncl.ac.uk
Laura E WadkinNUAcT Fellow, Newcastle UniversityVerified email at newcastle.ac.uk
Umberto PicchiniDept. Mathematical Sciences, University of Gothenburg and Chalmers University of TechnologyVerified email at chalmers.se
Thomas Von ZglinickiNewcastle University and Near East University Nicosia, Northern CyprusVerified email at ncl.ac.uk
John R. SpeakmanChinese Academy of Sciences, SIAT and IGDB and University of AberdeenVerified email at abdn.ac.uk
Christopher DrovandiProfessor of Statistics, Queensland University of TechnologyVerified email at qut.edu.au
Richard G. EverittUniversity of WarwickVerified email at warwick.ac.uk
Alexandre ThieryAssociate Professor, National University of Singapore (NUS)Verified email at nus.edu.sg

Andrew Golightly

Durham University, UK

Verified email at durham.ac.uk - Homepage

Bayesian computation stochastic modelling computational systems biology infectious diseases


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Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo A Golightly, DJ Wilkinson Interface Focus 1 (6), 807-820, 2011	355	2011
Bayesian inference for stochastic kinetic models using a diffusion approximation A Golightly, DJ Wilkinson Biometrics 61 (3), 781-788, 2005	271	2005
Bayesian inference for nonlinear multivariate diffusion models observed with error A Golightly, DJ Wilkinson Computational Statistics & Data Analysis 52 (3), 1674-1693, 2008	269	2008
Bayesian sequential inference for nonlinear multivariate diffusions A Golightly, DJ Wilkinson Statistics and Computing 16, 323-338, 2006	169	2006
Bayesian sequential inference for stochastic kinetic biochemical network models A Golightly, DJ Wilkinson Journal of Computational Biology 13 (3), 838-851, 2006	141	2006
Delayed acceptance particle MCMC for exact inference in stochastic kinetic models A Golightly, DA Henderson, C Sherlock Statistics and Computing 25 (5), 1039-1055, 2015	94	2015
Black-box variational inference for stochastic differential equations T Ryder, A Golightly, AS McGough, D Prangle International Conference on Machine Learning, 4423-4432, 2018	73	2018
Adaptive, delayed-acceptance MCMC for targets with expensive likelihoods C Sherlock, A Golightly, DA Henderson Journal of Computational and Graphical Statistics 26 (2), 434-444, 2017	63	2017
Improved bridge constructs for stochastic differential equations GA Whitaker, A Golightly, RJ Boys, C Sherlock Statistics and Computing 27, 885-900, 2017	45	2017
Bayesian inference for Markov jump processes with informative observations A Golightly, DJ Wilkinson Statistical applications in genetics and molecular biology 14 (2), 169-188, 2015	43	2015
Markov chain Monte Carlo algorithms for SDE parameter estimation DJ Wilkinson, A Golightly Learning and inference in computational systems biology, 253-275, 2010	41*	2010
Bayesian inference for diffusion-driven mixed-effects models GA Whitaker, A Golightly, RJ Boys, C Sherlock	33	2017
Bayesian inference for generalized stochastic population growth models with application to aphids CS Gillespie, A Golightly Journal of the Royal Statistical Society Series C: Applied Statistics 59 (2 …, 2010	33	2010
Simulation of stochastic kinetic models A Golightly, CS Gillespie In Silico Systems Biology, 169-187, 2013	31	2013
Ensemble MCMC: accelerating pseudo-marginal MCMC for state space models using the ensemble Kalman filter C Drovandi, RG Everitt, A Golightly, D Prangle Bayesian Analysis 17 (1), 223-260, 2022	24	2022
Gross energy metabolism in mice under late onset, short term caloric restriction KM Cameron, A Golightly, S Miwa, J Speakman, R Boys, T von Zglinicki Mechanisms of ageing and development, 2011	24	2011
Bayesian inference for hybrid discrete-continuous stochastic kinetic models C Sherlock, A Golightly, CS Gillespie Inverse Problems 30 (11), 114005, 2014	23	2014
Efficiency of delayed-acceptance random walk Metropolis algorithms C Sherlock, AH Thiery, A Golightly The Annals of Statistics 49 (5), 2972-2990, 2021	22	2021
Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms S Wiqvist, A Golightly, AT McLean, U Picchini Computational Statistics & Data Analysis 157, 107151, 2021	20	2021
Efficient schemes for stochastic kinetic models A Golightly, T Kypraios Statistics and Computing 28 (6), 1215-1230, 2018	20	2018

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