Corpus ID: 210700450

Approximate Weighted First-Order Model Counting: Exploiting Fast Approximate Model Counters and Symmetry

@article{Bremen2020ApproximateWF,
  title={Approximate Weighted First-Order Model Counting: Exploiting Fast Approximate Model Counters and Symmetry},
  author={Timothy van Bremen and Ondrej Kuzelka},
  journal={ArXiv},
  year={2020},
  volume={abs/2001.05263}
}
  • Timothy van Bremen, Ondrej Kuzelka
  • Published in ArXiv 2020
  • Computer Science
  • We study the symmetric weighted first-order model counting task and present ApproxWFOMC, a novel anytime method for efficiently bounding the weighted first-order model count in the presence of an unweighted first-order model counting oracle. The algorithm has applications to inference in a variety of first-order probabilistic representations, such as Markov logic networks and probabilistic logic programs. Crucially for many applications, we make no assumptions on the form of the input sentence… CONTINUE READING

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