Lifted Inference in 2 Variable Markov Logic Networks with Function and Cardinality Constraints Using Discrete Fourier Transform
In this paper we show that inference in 2 variable Markov logic networks (MLNs) with cardinality and function constraints is domain liftable. To obtain this result we use existing domain lifted algorithms for weighted first order model counting (Van den Broeck et al, KR 2014) together with discrete Fourier transform of certain distributions associated to MLNs.
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