bayesian-deep-learning

This position paper argues that sampling-based inference in Bayesian neural networks has achieved computational parity with optimization-based methods and is poised to supersede them, offering superior uncertainty quantification and prediction performance.

bde is a Python package that brings sampling-based Bayesian Deep Learning to practitioners via the MILE method, combining JAX's speed with scikit-learn's API for tabular supervised learning tasks.