Chris Sherlock

11 papers Journal 11
YearRankTypeTitle / Venue / Authors
2024 J jnl
Scalable Monte Carlo for Bayesian Learning.
CoRR
Paul Fearnhead, Christopher Nemeth, Chris J. Oates, Chris Sherlock
2023 J jnl
Accelerating inference for stochastic kinetic models.
Comput. Stat. Data Anal.
Tom E. Lowe, Andrew Golightly, Chris Sherlock
2023 J jnl
Exact Bayesian Inference for Discretely Observed Markov Jump Processes Using Finite Rate Matrices.
J. Comput. Graph. Stat.
Chris Sherlock, Andrew Golightly
2023 J jnl
The Apogee to Apogee Path Sampler.
J. Comput. Graph. Stat.
Chris Sherlock, Szymon Urbas, Matthew Ludkin
2022 J jnl
Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes.
Stat. Comput.
Andrew Golightly, Chris Sherlock
2021 J jnl
Direct statistical inference for finite Markov jump processes via the matrix exponential.
Comput. Stat.
Chris Sherlock
2020 J jnl
Motor unit number estimation via sequential Monte Carlo.
Comput. Stat. Data Anal.
Simon A. C. Taylor, Chris Sherlock, Gareth Ridall, Paul Fearnhead
2019 J jnl
Efficient sampling of conditioned Markov jump processes.
Stat. Comput.
Andrew Golightly, Chris Sherlock
2017 J jnl
Improved bridge constructs for stochastic differential equations.
Stat. Comput.
Gavin A. Whitaker, Andrew Golightly, Richard J. Boys, Chris Sherlock
2015 J jnl
Delayed acceptance particle MCMC for exact inference in stochastic kinetic models.
Stat. Comput.
Andrew Golightly, Daniel A. Henderson, Chris Sherlock
2013 J jnl
Optimal Scaling of the Random Walk Metropolis: General Criteria for the 0.234 Acceptance Rule.
J. Appl. Probab.
Chris Sherlock