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Factor Graph Grammars

David Chiang, Darcey Riley

Spotlight presentation: Orals & Spotlights Track 25: Probabilistic Models/Statistics
on Thu, Dec 10th, 2020 @ 15:30 – 15:40 GMT
Poster Session 6 (more posters)
on Thu, Dec 10th, 2020 @ 17:00 – 19:00 GMT
Abstract: We propose the use of hyperedge replacement graph grammars for factor graphs, or actor graph grammars (FGGs) for short. FGGs generate sets of factor graphs and can describe a more general class of models than plate notation, dynamic graphical models, case-factor diagrams, and sum-product networks can. Moreover, inference can be done on FGGs without enumerating all the generated factor graphs. For finite variable domains (but possibly infinite sets of graphs), a generalization of variable elimination to FGGs allows exact and tractable inference in many situations. For finite sets of graphs (but possibly infinite variable domains), a FGG can be converted to a single factor graph amenable to standard inference techniques.

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