3 citations · 10 across the 12 of their papers we have counts for
3 papers · 1 filter
Exact Bayesian Inference for Loopy Probabilistic Programs using Generating Functions
Lutz Klinkenberg, Christian Blumenthal, Mingshuai Chen +2
We present an exact Bayesian inference method for inferring posterior distributions encoded by probabilistic programs featuring possibly unbounded loops. Our method is built on a d…
Lower Bounds for Possibly Divergent Probabilistic Programs
Shenghua Feng, Mingshuai Chen, Han Su +3
We present a new proof rule for verifying lower bounds on quantities of probabilistic programs. Our proof rule is not confined to almost-surely terminating programs -- as is the ca…
Exact Probabilistic Inference Using Generating Functions
Lutz Klinkenberg, Tobias Winkler, Mingshuai Chen +1
Probabilistic programs are typically normal-looking programs describing posterior probability distributions. They intrinsically code up randomized algorithms and have long been at…