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@inproceedings{CFMV15,
  title={From Weighted to Unweighted Model Counting},
  url={../Papers/ijcai15.pdf},
  code={https://bitbucket.org/kuldeepmeel/weightcount},
  author={
    Chakraborty, Supratik and Fried, Dror and Meel, Kuldeep S. and Vardi, Moshe
    Y.
  },
  booktitle=IJCAI,
  year={2015},
  month=jul,
  bib2html_rescat={Counting},
  bib2html_pubtype={Refereed Conference},
  abstract={
    The recent surge of interest in reasoning about
    probabilistic graphical models has led to the development
    of various techniques for probabilistic
    reasoning. Of these, techniques based on weighted
    model counting are particularly interesting since
    they can potentially leverage recent advances in unweighted
    model counting and in propositional satisfiability
    solving. In this paper, we present a new
    approach to weighted model counting via reduction
    to unweighted model counting. Our reduction,
    which is polynomial-time and preserves the normal
    form (CNF/DNF) of the input formula, allows us
    to exploit advances in unweighted model counting
    to solve weighted model counting instances. Experiments
    with weighted model counters built using
    our reduction indicate that these counters performs
    much better than a state-of-the-art weighted model
    counter.
  },
}