140 citations · 341 across the 21 of their papers we have counts for
Showing 2015 · stat.MLShow all
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stat.ML2015★ 4 cited
A New Approach to Probabilistic Programming Inference
Frank Wood, Jan Willem van de Meent, Vikash Mansinghka
We introduce and demonstrate a new approach to inference in expressive probabilistic programming languages based on particle Markov chain Monte Carlo. Our approach is simple to imp…
stat.ML2015★ 15 cited
Particle Gibbs with Ancestor Sampling for Probabilistic Programs
Jan-Willem van de Meent, Hongseok Yang, Vikash Mansinghka +1
Particle Markov chain Monte Carlo techniques rank among current state-of-the-art methods for probabilistic program inference. A drawback of these techniques is that they rely on im…