12 citations · 39 across the 16 of their papers we have counts for
4 papers · 1 filter
Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data
Aayush Mishra, Daniel Habermann, Marvin Schmitt +2
Amortized Bayesian inference (ABI) with neural networks can solve probabilistic inverse problems orders of magnitude faster than classical methods. However, ABI is not yet sufficie…
Amortized Bayesian Multilevel Models
Daniel Habermann, Marvin Schmitt, Lars Kühmichel +3
Multilevel models (MLMs) are a central building block of the Bayesian workflow. They enable joint, interpretable modeling of data across hierarchical levels and provide a fully pro…
Sensitivity-Aware Amortized Bayesian Inference
Lasse Elsemüller, Hans Olischläger, Marvin Schmitt +3
Sensitivity analyses reveal the influence of various modeling choices on the outcomes of statistical analyses. While theoretically appealing, they are overwhelmingly inefficient fo…
Meta-Uncertainty in Bayesian Model Comparison
Marvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner
Bayesian model comparison (BMC) offers a principled probabilistic approach to study and rank competing models. In standard BMC, we construct a discrete probability distribution ove…