5 citations · 5 across the 3 of their papers we have counts for
3 papers
Incremental Computation for Efficient Programmable Inference in Probabilistic Programs
Fabian Zaiser, Jack Czenszak, Martin C. Rinard +2
Inference in probabilistic programs generally requires evaluating many possible program executions to find those of high posterior density. To scale inference to large datasets, it…
Human agency in initial human-AI proof formalization workflows
Katherine M. Collins, Simon Frieder, Jonas Bayer +14
For centuries, human mathematicians have written proofs to substantiate their mathematical arguments; yet, the ability to automatically verify the validity of proofs has long been…
Guaranteed Bounds on Posterior Distributions of Discrete Probabilistic Programs with Loops
Fabian Zaiser, Andrzej S. Murawski, C. -H. Luke Ong
We study the problem of bounding the posterior distribution of discrete probabilistic programs with unbounded support, loops, and conditioning. Loops pose the main difficulty in th…