70 citations · 466 across the 19 of their papers we have counts for
19 papers · 1 filter
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…
Identifying Independencies in Causal Graphs with Feedback
Judea Pearl, Rina Dechter
We show that the d -separation criterion constitutes a valid test for conditional independence relationships that are induced by feedback systems involving discrete variables.
An Evaluation of Structural Parameters for Probabilistic Reasoning: Results on Benchmark Circuits
Yousri El Fattah, Rina Dechter
Many algorithms for processing probabilistic networks are dependent on the topological properties of the problem's structure. Such algorithms (e.g., clustering, conditioning) are e…
Topological Parameters for Time-Space Tradeoff
Rina Dechter
In this paper we propose a family of algorithms combining tree-clustering with conditioning that trade space for time. Such algorithms are useful for reasoning in probabilistic and…
Bucket Elimination: A Unifying Framework for Several Probabilistic Inference
Rina Dechter
Probabilistic inference algorithms for finding the most probable explanation, the maximum aposteriori hypothesis, and the maximum expected utility and for updating belief are refor…
A Scheme for Approximating Probabilistic Inference
Rina Dechter, Irina Rish
This paper describes a class of probabilistic approximation algorithms based on bucket elimination which offer adjustable levels of accuracy and efficiency. We analyze the approxim…