2 citations · 6 across the 6 of their papers we have counts for
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cs.PL2021★ 1 cited
Sound Probabilistic Inference via Guide Types
Di Wang, Jan Hoffmann, Thomas Reps
Probabilistic programming languages aim to describe and automate Bayesian modeling and inference. Modern languages support programmable inference, which allows users to customize i…
cs.PL2021★ 2 cited
Expected-Cost Analysis for Probabilistic Programs and Semantics-Level Adaption of Optional Stopping Theorems
Di Wang, Jan Hoffmann, Thomas Reps
In this article, we present a semantics-level adaption of the Optional Stopping Theorem, sketch an expected-cost analysis as its application, and survey different variants of the O…