9 citations · 13 across the 6 of their papers we have counts for
Showing cs.AIShow all
2 papers · 1 filter
cs.AI2026
A Computationally Feasible Framework for Causal Probabilistic Explanation
Rafal Urbaniak, Sam Witty, Daniel Waxman +7
Explaining why a specific outcome occurred, and which inputs deserve the blame or credit, is central to philosophical, scientific, and policy analysis. Existing tools split into tw…
cs.AI2023★ 3 cited
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…