Lifted Inference for Probabilistic Programming

نویسندگان

  • Wannes Meert
  • Guy Van den Broeck
  • Nima Taghipour
  • Daan Fierens
  • Hendrik Blockeel
  • Jesse Davis
  • Luc De Raedt
چکیده

A probabilistic program often gives rise to a complicated underlying probabilistic model. Performing inference in such a model is challenging. One solution to this problem is lifted inference which improves tractability by exploiting symmetries in the underlying model. Our group is pursuing a lifted approach to inference for probabilistic logic programs.

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تاریخ انتشار 2012