Andrew Golightly

According to our database, Andrew Golightly authored at least 22 papers between 2002 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Bayesian inference for a spatio-temporal model of road traffic collision data.

Nicola Hewett, Andrew Golightly, Lee Fawcett, Neil Thorpe

J. Comput. Sci., 2024

2023

Accelerating Bayesian inference for stochastic epidemic models using incidence data.

Andrew Golightly, Laura E. Wadkin, Sam A. Whitaker, Andrew W. Baggaley, Nick G. Parker, Theodore Kypraios

Stat. Comput., December, 2023

Accelerating inference for stochastic kinetic models.

Tom E. Lowe, Andrew Golightly, Chris Sherlock

Comput. Stat. Data Anal., September, 2023

Exact Bayesian Inference for Discretely Observed Markov Jump Processes Using Finite Rate Matrices.

Chris Sherlock, Andrew Golightly

J. Comput. Graph. Stat., January, 2023

A sparse Bayesian hierarchical vector autoregressive model for microbial dynamics in a wastewater treatment plant.

Naomi E. Hannaford, Sarah E. Heaps, Tom M. W. Nye, Thomas P. Curtis, Ben Allen, Andrew Golightly, Darren J. Wilkinson

Comput. Stat. Data Anal., 2023

2022

Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes.

Andrew Golightly, Chris Sherlock

Stat. Comput., 2022

2021

Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms.

Samuel Wiqvist, Andrew Golightly, Ashleigh T. McLean, Umberto Picchini

Comput. Stat. Data Anal., 2021

The neural moving average model for scalable variational inference of state space models.

Thomas Ryder, Dennis Prangle, Andrew Golightly, Isaac Matthews

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Sequential Bayesian inference for spatio-temporal models of temperature and humidity data.

Yingying Lai, Andrew Golightly, Richard J. Boys

J. Comput. Sci., 2020

2019

Efficient sampling of conditioned Markov jump processes.

Andrew Golightly, Chris Sherlock

Stat. Comput., 2019

Correlated pseudo-marginal schemes for time-discretised stochastic kinetic models.

Andrew Golightly, Emma Bradley, Tom E. Lowe, Colin S. Gillespie

Comput. Stat. Data Anal., 2019

Scalable approximate inference for state space models with normalising flows.

Tom Ryder, Andrew Golightly, Isaac Matthews, Dennis Prangle

CoRR, 2019

2018

Efficient SMC² schemes for stochastic kinetic models.

Andrew Golightly, Theodore Kypraios

Stat. Comput., 2018

Black-Box Autoregressive Density Estimation for State-Space Models.

Tom Ryder, Andrew Golightly, A. Stephen McGough, Dennis Prangle

CoRR, 2018

Black-Box Variational Inference for Stochastic Differential Equations.

Thomas Ryder, Andrew Golightly, A. Stephen McGough, Dennis Prangle

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Improved bridge constructs for stochastic differential equations.

Gavin A. Whitaker, Andrew Golightly, Richard J. Boys, Chris Sherlock

Stat. Comput., 2017

2015

Delayed acceptance particle MCMC for exact inference in stochastic kinetic models.

Andrew Golightly, Daniel A. Henderson, Chris Sherlock

Stat. Comput., 2015

2010

Markov Chain Monte Carlo Algorithms for SDE Parameter Estimation.

Darren J. Wilkinson, Andrew Golightly

Proceedings of the Learning and Inference in Computational Systems Biology., 2010

2008

Bayesian inference for nonlinear multivariate diffusion models observed with error.

Andrew Golightly, Darren J. Wilkinson

Comput. Stat. Data Anal., 2008

2006

Bayesian sequential inference for nonlinear multivariate diffusions.

Andrew Golightly, Darren J. Wilkinson

Stat. Comput., 2006

Bayesian Sequential Inference for Stochastic Kinetic Biochemical Network Models.

Andrew Golightly, Darren J. Wilkinson

J. Comput. Biol., 2006

2002

An experimental speech to graphics system.

Andrew Golightly, Tony Smith

Proceedings of the SIGCHI-NZ Symposium on Computer-Human Interaction, 2002