83 citations · 108 across the 14 of their papers we have counts for
4 papers · 1 filter
Bit Blasting Probabilistic Programs
Poorva Garg, Steven Holtzen, Guy Van den Broeck +1
Probabilistic programming languages (PPLs) are expressive means for creating and reasoning about probabilistic models. Unfortunately hybrid probabilistic programs, involving both c…
Scaling Integer Arithmetic in Probabilistic Programs
William X. Cao, Poorva Garg, Ryan Tjoa +3
Distributions on integers are ubiquitous in probabilistic modeling but remain challenging for many of today's probabilistic programming languages (PPLs). The core challenge comes f…
Lilac: A Modal Separation Logic for Conditional Probability
John M. Li, Amal Ahmed, Steven Holtzen
We present Lilac, a separation logic for reasoning about probabilistic programs where separating conjunction captures probabilistic independence. Inspired by an analogy with mutabl…
Type Prediction With Program Decomposition and Fill-in-the-Type Training
Federico Cassano, Ming-Ho Yee, Noah Shinn +2
TypeScript and Python are two programming languages that support optional type annotations, which are useful but tedious to introduce and maintain. This has motivated automated typ…