140 citations · 735 across the 46 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★ 7 cited
Learning Probabilistic Programs
Yura N. Perov, Frank D. Wood
We develop a technique for generalising from data in which models are samplers represented as program text. We establish encouraging empirical results that suggest that Markov chai…
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…