#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.
· Neural Information Processin... · 65 citations
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