113 citations · 491 across the 32 of their papers we have counts for
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cs.PL2015
Abstraction Refinement Guided by a Learnt Probabilistic Model
Radu Grigore, Hongseok Yang
The core challenge in designing an effective static program analysis is to find a good program abstraction -- one that retains only details relevant to a given query. In this paper…
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…