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2020 – today
- 2024
[j16]Nicola Hewett
, Andrew Golightly, Lee Fawcett, Neil Thorpe:
Bayesian inference for a spatio-temporal model of road traffic collision data. J. Comput. Sci. 80: 102326 (2024)- 2023
- [j15]Naomi E. Hannaford, Sarah E. Heaps, Tom M. W. Nye, Thomas P. Curtis, Ben Allen, Andrew Golightly, Darren J. Wilkinson:
A sparse Bayesian hierarchical vector autoregressive model for microbial dynamics in a wastewater treatment plant. Comput. Stat. Data Anal. 179: 107659 (2023) - [j14]Tom E. Lowe, Andrew Golightly, Chris Sherlock:
Accelerating inference for stochastic kinetic models. Comput. Stat. Data Anal. 185: 107760 (2023) - [j13]Chris Sherlock, Andrew Golightly:
Exact Bayesian Inference for Discretely Observed Markov Jump Processes Using Finite Rate Matrices. J. Comput. Graph. Stat. 32(1): 36-48 (2023) - [j12]Andrew Golightly, Laura E. Wadkin, Sam A. Whitaker, Andrew W. Baggaley, Nick G. Parker, Theodore Kypraios:
Accelerating Bayesian inference for stochastic epidemic models using incidence data. Stat. Comput. 33(6): 134 (2023) - 2022
- [j11]Andrew Golightly, Chris Sherlock:
Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes. Stat. Comput. 32(1): 21 (2022) - 2021
- [j10]Samuel Wiqvist, Andrew Golightly, Ashleigh T. McLean, Umberto Picchini:
Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms. Comput. Stat. Data Anal. 157: 107151 (2021) - [c3]Thomas Ryder, Dennis Prangle, Andrew Golightly, Isaac Matthews:
The neural moving average model for scalable variational inference of state space models. UAI 2021: 12-22 - 2020
- [j9]Yingying Lai, Andrew Golightly, Richard J. Boys:
Sequential Bayesian inference for spatio-temporal models of temperature and humidity data. J. Comput. Sci. 43: 101125 (2020)
2010 – 2019
- 2019
- [j8]Andrew Golightly, Emma Bradley, Tom E. Lowe, Colin S. Gillespie:
Correlated pseudo-marginal schemes for time-discretised stochastic kinetic models. Comput. Stat. Data Anal. 136: 92-107 (2019) - [j7]Andrew Golightly, Chris Sherlock:
Efficient sampling of conditioned Markov jump processes. Stat. Comput. 29(5): 1149-1163 (2019) - [i2]Tom Ryder, Andrew Golightly, Isaac Matthews, Dennis Prangle:
Scalable approximate inference for state space models with normalising flows. CoRR abs/1910.00879 (2019) - 2018
- [j6]Andrew Golightly, Theodore Kypraios:
Efficient SMC2 schemes for stochastic kinetic models. Stat. Comput. 28(6): 1215-1230 (2018) - [c2]Thomas Ryder, Andrew Golightly, A. Stephen McGough, Dennis Prangle:
Black-Box Variational Inference for Stochastic Differential Equations. ICML 2018: 4420-4429 - [i1]Tom Ryder, Andrew Golightly, A. Stephen McGough, Dennis Prangle:
Black-Box Autoregressive Density Estimation for State-Space Models. CoRR abs/1811.08337 (2018) - 2017
- [j5]Gavin A. Whitaker, Andrew Golightly, Richard J. Boys, Chris Sherlock:
Improved bridge constructs for stochastic differential equations. Stat. Comput. 27(4): 885-900 (2017) - 2015
- [j4]Andrew Golightly, Daniel A. Henderson, Chris Sherlock:
Delayed acceptance particle MCMC for exact inference in stochastic kinetic models. Stat. Comput. 25(5): 1039-1055 (2015) - 2010
- [p1]Darren J. Wilkinson, Andrew Golightly:
Markov Chain Monte Carlo Algorithms for SDE Parameter Estimation. Learning and Inference in Computational Systems Biology 2010: 253-276
2000 – 2009
- 2008
- [j3]Andrew Golightly, Darren J. Wilkinson:
Bayesian inference for nonlinear multivariate diffusion models observed with error. Comput. Stat. Data Anal. 52(3): 1674-1693 (2008) - 2006
- [j2]Andrew Golightly, Darren J. Wilkinson:
Bayesian Sequential Inference for Stochastic Kinetic Biochemical Network Models. J. Comput. Biol. 13(3): 838-851 (2006) - [j1]Andrew Golightly, Darren J. Wilkinson:
Bayesian sequential inference for nonlinear multivariate diffusions. Stat. Comput. 16(4): 323-338 (2006) - 2002
- [c1]Andrew Golightly, Tony Smith:
An experimental speech to graphics system. CHINZ 2002: 91-96
Coauthor Index
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