Tag: Bayesian Deep Learning

AI Machine Learning & Data Science Research

New Study Revisits Laplace Approximation, Validating It as an ‘Effortless’ Method for Bayesian Deep Learning

In the new paper Laplace Redux — Effortless Bayesian Deep Learning, a research team from the University of Cambridge, University of Tübingen, ETH Zurich and DeepMind conducts extensive experiments demonstrating that the Laplace approximation (LA) is a simple and cost-efficient yet competitive approximation method for inference in Bayesian deep learning.