Lifted Inference in 2-Variable Markov Logic Networks with Function and Cardinality Constraints Using Discrete Fourier Transform

Markov logic networks (MLNs, Richardson and Domingos, 2006) are a statistical relational learning [Getoor and Taskar, 2007] framework for probabilistic modelling of complex relational structures such as social and biological networks, molecules etc. In general, inference in MLNs is intractable. Lifted inference refers to a set of methods developed in the literature which exploit symmetries for making probabilistic inference more tractable, e.g.