2 papers
cs.LG2021
Control-Data Separation and Logical Condition Propagation for Efficient Inference on Probabilistic Programs
Ichiro Hasuo, Yuichiro Oyabu, Clovis Eberhart +3
We present a novel sampling framework for probabilistic programs. The framework combines two recent ideas -- \emph{control-data separation} and \emph{logical condition propagation}…
cs.PL2018
Ranking and Repulsing Supermartingales for Reachability in Probabilistic Programs
Toru Takisaka, Yuichiro Oyabu, Natsuki Urabe +1
Computing reachability probabilities is a fundamental problem in the analysis of probabilistic programs. This paper aims at a comprehensive and comparative account on various marti…