208 citations · 963 across the 30 of their papers we have counts for
Showing 2014Show all
3 papers · 1 filter
stat.CO2014★ 21 cited
Asynchronous Anytime Sequential Monte Carlo
Brooks Paige, Frank Wood, Arnaud Doucet +1
We introduce a new sequential Monte Carlo algorithm we call the particle cascade. The particle cascade is an asynchronous, anytime alternative to traditional particle filtering alg…
cs.AI2014★ 38 cited
A Compilation Target for Probabilistic Programming Languages
Brooks Paige, Frank Wood
Forward inference techniques such as sequential Monte Carlo and particle Markov chain Monte Carlo for probabilistic programming can be implemented in any programming language by cr…
stat.ML2014★ 4 cited
Tempering by Subsampling
Jan-Willem van de Meent, Brooks Paige, Frank Wood
In this paper we demonstrate that tempering Markov chain Monte Carlo samplers for Bayesian models by recursively subsampling observations without replacement can improve the perfor…