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arXiv · 2605.14146

bde: A Python Package for Bayesian Deep Ensembles via MILE

Vyron Arvanitis·Angelos Aslanidis·Emanuel Sommer·David Rügamer
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Abstract

bde is a user-friendly Python package for Bayesian Deep Ensembles with a particular focus on tabular data. Built on an efficient JAX implementation of the sampling-based inference method Microcanonical Langevin Ensembles (MILE), it provides scikit-learn compatible estimators for fast training, efficient Markov Chain Monte Carlo sampling, and uncertainty quantification in both regression and classification tasks.

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Vyron Arvanitis, Angelos Aslanidis, Emanuel Sommer, David Rügamer. 2026-05-13. bde: A Python Package for Bayesian Deep Ensembles via MILE. https://doi.org/10.21105/joss.10653

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