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stat.ML2025
AutoBayes: A Compositional Framework for Generalized Variational Inference
Toby St Clere Smithe, Marco Perin
We introduce a new compositional framework for generalized variational inference, clarifying the different parts of a model, how they interact, and how they compose. We explain tha…
math.ST2025
On the Functoriality of Belief Propagation Algorithms on finite Partially Ordered Sets
Grégoire Sergeant-Perthuis, Toby St Clere Smithe, Léo Boitel
Undirected graphical models are a widely used class of probabilistic models in machine learning that capture prior knowledge or putative pairwise interactions between variables. Th…