Amortized Bayesian Inference on Multilevel Models of Arbitrary Structure
We develop a general method for amortized Bayesian inference on multilevel models of arbitrary structure. Given a generative model specified as a directed acyclic graph, our method automatically derives valid factorizations of the joint posterior and matching neural network architectures. The key steps, graph expansion...
Daniel Habermann, Andreas Bulling, Stefan T. Radev et al.
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