6 citations · 8 across the 2 of their papers we have counts for
3 papers
cs.LO2018
Constraint-Based Inference in Probabilistic Logic Programs
Arun Nampally, Timothy Zhang, C. R. Ramakrishnan
Probabilistic Logic Programs (PLPs) generalize traditional logic programs and allow the encoding of models combining logical structure and uncertainty. In PLP, inference is perform…
cs.AI2016★ 2 cited
Inference in Probabilistic Logic Programs using Lifted Explanations
Arun Nampally, C. R. Ramakrishnan
In this paper, we consider the problem of lifted inference in the context of Prism-like probabilistic logic programming languages. Traditional inference in such languages involves…
cs.AI2014★ 6 cited
Adaptive MCMC-Based Inference in Probabilistic Logic Programs
Arun Nampally, C. R. Ramakrishnan
Probabilistic Logic Programming (PLP) languages enable programmers to specify systems that combine logical models with statistical knowledge. The inference problem, to determine th…