3 citations · 4 across the 5 of their papers we have counts for
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stat.CO2019★ 3 cited
Scalable Bayesian Inference for Population Markov Jump Processes
Iker Perez, Theodore Kypraios
Bayesian inference for Markov jump processes (MJPs) where available observations relate to either system states or jumps typically relies on data-augmentation Markov Chain Monte Ca…
stat.CO2018
On Bayesian inferential tasks with infinite-state jump processes: efficient data augmentation
Iker Perez, Lax Chan, Mercedes Torres Torres +2
Advances in sampling schemes for Markov jump processes have recently enabled multiple inferential tasks. However, in statistical and machine learning applications, we often require…
stat.CO2017★ 1 cited
Auxiliary Variables for Bayesian Inference in Multi-Class Queueing Networks
Iker Perez, David Hodge, Theodore Kypraios
Queue networks describe complex stochastic systems of both theoretical and practical interest. They provide the means to assess alterations, diagnose poor performance and evaluate…