231 citations · 312 across the 21 of their papers we have counts for
4 papers · 1 filter
Likelihood free inference for Markov processes: a comparison
Jamie Owen, Darren J. Wilkinson, Colin S. Gillespie
Approaches to Bayesian inference for problems with intractable likelihoods have become increasingly important in recent years. Approximate Bayesian computation (ABC) and "likelihoo…
Bayesian inference for Markov jump processes with informative observations
Andrew Golightly, Darren J. Wilkinson
In this paper we consider the problem of parameter inference for Markov jump process (MJP) representations of stochastic kinetic models. Since transition probabilities are intracta…
Bayesian identification of protein differential expression in multi-group isobaric labelled mass spectrometry data
Howsun Jow, Richard J. Boys, Darren J. Wilkinson
In this paper we develop a Bayesian statistical inference approach to the unified analysis of isobaric labelled MS/MS proteomic data across multiple experiments. An explicit probab…
Scalable Inference for Markov Processes with Intractable Likelihoods
Jamie Owen, Darren J. Wilkinson, Colin S. Gillespie
Bayesian inference for Markov processes has become increasingly relevant in recent years. Problems of this type often have intractable likelihoods and prior knowledge about model r…