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Laurent Charlin

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#machine learning May 2023

Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network

This paper proposes a method to approximate the joint posterior over not only the structure of a Bayesian Network, but also the parameters of its conditional probability distributions, using a single GFlowNet whose sampling policy follows a two-phase process.

T. Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian et al. · 65 citations · ⚡4