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pro vyhledávání: '"Mattei, Lilith"'
Belief revision is the task of modifying a knowledge base when new information becomes available, while also respecting a number of desirable properties. Classical belief revision schemes have been already specialised to \emph{binary decision diagram
Externí odkaz:
http://arxiv.org/abs/2201.08112
Publikováno v:
4th Workshop on Tractable Probabilistic Modeling (TPM 2021)
Probabilistic sentential decision diagrams are a class of structured-decomposable probabilistic circuits especially designed to embed logical constraints. To adapt the classical LearnSPN scheme to learn the structure of these models, we propose a new
Externí odkaz:
http://arxiv.org/abs/2107.12130
Autor:
Mattei, Lilith, Antonucci, Alessandro, Mauá, Denis Deratani, Facchini, Alessandro, Llerena, Julissa Villanueva
Probabilistic sentential decision diagrams are logic circuits where the inputs of disjunctive gates are annotated by probability values. They allow for a compact representation of joint probability mass functions defined over sets of Boolean variable
Externí odkaz:
http://arxiv.org/abs/2008.08524