3 papers
cs.AI2017
Exact Inference for Relational Graphical Models with Interpreted Functions: Lifted Probabilistic Inference Modulo Theories
Rodrigo de Salvo Braz, Ciaran O'Reilly
Probabilistic Inference Modulo Theories (PIMT) is a recent framework that expands exact inference on graphical models to use richer languages that include arithmetic, equalities, a…
cs.AI2017
Anytime Exact Belief Propagation
Gabriel Azevedo Ferreira, Quentin Bertrand, Charles Maussion +1
Statistical Relational Models and, more recently, Probabilistic Programming, have been making strides towards an integration of logic and probabilistic reasoning. A natural expecta…
cs.AI2016
Probabilistic Inference Modulo Theories
Rodrigo de Salvo Braz, Ciaran O'Reilly, Vibhav Gogate +1
We present SGDPLL(T), an algorithm that solves (among many other problems) probabilistic inference modulo theories, that is, inference problems over probabilistic models defined vi…