[R] 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.

Here is a quick read: New Study Revisits Laplace Approximation, Validating It as an 'Effortless' Method for Bayesian Deep Learning.

The Laplace code is available on the project’s GitHub. …

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