Introducing probabilistic sentential decision diagrams and their credal extension
13 February 2020 - 13 February 2020
Manno, Galleria 1, 2nd floor, room G1-201 @12:00
Probabilistic sentential decision diagrams are a class of probabilistic graphical models natively embedding logical constraints within a “deep” layered structure with statistical parameters. They thence induce a joint probability distribution over the involved Boolean variables that sharply assigns probability zero to states inconsistent with the logical constraints. In this presentation, I will first introduce and motivate such probabilistic circuits. I will then present a set-valued generalisation of the probabilistic quantification in these models, that allows to replace the sharp specification of the local probabilities with linear constraints over them, In doing so, a (convex) set of joint probability mass functions, all consistent with the assigned logical constraints, is induced.

The speakers

Lilith Mattei graduated in pure mathematics at EPFL. After a period of teaching in high school, in 2018 she started working at IDSIA as a research assistant. She is currently a PhD student under the supervision of Alessandro Antonucci and Alessandro Facchini. Her research is in PGMs and logic.