bde: A Python Package for Bayesian Deep Ensembles via MILE
cs.LG updates on arXiv.org
Vyron Arvanitis, Angelos Aslanidis, Emanuel Sommer, David R\"ugamer
arXiv:2605.14146v1 Announce Type: new 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.
