Author

Paul-Christian Burkner

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#machine learning Preprint Sep 2026

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. · 0 citations

#machine learning Preprint Sep 2026

High-Dimensional Simulation-Based Inference in Latent Spaces

Neural simulation-based inference (SBI) has been widely successful in inferring a relatively small number of interpretable parameters from potentially high-dimensional observations, such as images or time series. Accordingly, representation learning in SBI has focused almost exclusively on compressing the observations...

Lars Kuhmichel, Stefan T. Radev, B. Koppolu et al. · 0 citations