bde: A Python Package for Bayesian Deep Ensembles via MILE
机器学习
2026-05-15 v1
摘要
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.
关键词
引用
@article{arxiv.2605.14146,
title = {bde: A Python Package for Bayesian Deep Ensembles via MILE},
author = {Vyron Arvanitis and Angelos Aslanidis and Emanuel Sommer and David Rügamer},
journal= {arXiv preprint arXiv:2605.14146},
year = {2026}
}