12 citations · 39 across the 16 of their papers we have counts for
4 papers · 1 filter
Amortized Bayesian Workflow
Chengkun Li, Aki Vehtari, Paul-Christian Bürkner +3
Bayesian inference often faces a trade-off between computational speed and sampling accuracy. We propose an adaptive workflow that integrates rapid amortized inference with gold-st…
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…
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigation
Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe +1
Recent advances in probabilistic deep learning enable efficient amortized Bayesian inference in settings where the likelihood function is only implicitly defined by a simulation pr…
The Simplex Projection: Lossless Visualization of 4D Compositional Data on a 2D Canvas
Marvin Schmitt, Yuga Hikida, Stefan T Radev +2
The simplex projection expands the capabilities of simplex plots (also known as ternary plots) to achieve a lossless visualization of 4D compositional data on a 2D canvas. Previous…