Probabilistic Programming Interfaces for Random Graphs: Markov Categories, Graphons, and Nominal Sets

Probabilistic Programming Interfaces for Random Graphs: Markov Categories, Graphons, and Nominal Sets

We study semantic models of probabilistic programming languages over graphs, and establish a connection to graphons from graph theory and combinatorics. We show that every well-behaved equational theory for our graph probabilistic programming language corresponds to a graphon, and conversely, every...

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Bibliographic Details
Main Authors: Ackerman, Nate, Freer, Cameron E., Kaddar, Younesse, Karwowski, Jacek, Moss, Sean, Roy, Daniel, Staton, Sam, Yang, Hongseok
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:English
Published: ACM 2024
Online Access:https://hdl.handle.net/1721.1/153447

Internet

https://hdl.handle.net/1721.1/153447

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