Understanding the Complexity of Lifted Inference and Asymmetric Weighted Model Counting

13 May 2014 Eric Gribkoff Guy Van Den Broeck Dan Suciu

In this paper we study lifted inference for the Weighted First-Order Model Counting problem (WFOMC), which counts the assignments that satisfy a given sentence in first-order logic (FOL); it has applications in Statistical Relational Learning (SRL) and Probabilistic Databases (PDB). We present several results... (read more)

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