Andrew Golightly

Orcid: 0000-0001-6730-1279

According to our database1, Andrew Golightly authored at least 22 papers between 2002 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
Bayesian inference for a spatio-temporal model of road traffic collision data.
J. Comput. Sci., 2024

2023
Accelerating Bayesian inference for stochastic epidemic models using incidence data.
Stat. Comput., December, 2023

Accelerating inference for stochastic kinetic models.
Comput. Stat. Data Anal., September, 2023

Exact Bayesian Inference for Discretely Observed Markov Jump Processes Using Finite Rate Matrices.
J. Comput. Graph. Stat., January, 2023

A sparse Bayesian hierarchical vector autoregressive model for microbial dynamics in a wastewater treatment plant.
Comput. Stat. Data Anal., 2023

2022
Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes.
Stat. Comput., 2022

2021
Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms.
Comput. Stat. Data Anal., 2021

The neural moving average model for scalable variational inference of state space models.
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.
J. Comput. Sci., 2020

2019
Efficient sampling of conditioned Markov jump processes.
Stat. Comput., 2019

Correlated pseudo-marginal schemes for time-discretised stochastic kinetic models.
Comput. Stat. Data Anal., 2019

Scalable approximate inference for state space models with normalising flows.
CoRR, 2019

2018
Efficient SMC<sup>2</sup> schemes for stochastic kinetic models.
Stat. Comput., 2018

Black-Box Autoregressive Density Estimation for State-Space Models.
CoRR, 2018

Black-Box Variational Inference for Stochastic Differential Equations.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Improved bridge constructs for stochastic differential equations.
Stat. Comput., 2017

2015
Delayed acceptance particle MCMC for exact inference in stochastic kinetic models.
Stat. Comput., 2015

2010
Markov Chain Monte Carlo Algorithms for SDE Parameter Estimation.
Proceedings of the Learning and Inference in Computational Systems Biology., 2010

2008
Bayesian inference for nonlinear multivariate diffusion models observed with error.
Comput. Stat. Data Anal., 2008

2006
Bayesian sequential inference for nonlinear multivariate diffusions.
Stat. Comput., 2006

Bayesian Sequential Inference for Stochastic Kinetic Biochemical Network Models.
J. Comput. Biol., 2006

2002
An experimental speech to graphics system.
Proceedings of the SIGCHI-NZ Symposium on Computer-Human Interaction, 2002


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