Web: https://syncedreview.com/2022/01/25/deepmind-podracer-tpu-based-rl-frameworks-deliver-exceptional-performance-at-low-cost-192/

Jan. 25, 2022, 3:06 p.m. | Synced

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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.

The post New Study Revisits Laplace Approximation, Validating It as an ‘Effortless’ Method for Bayesian Deep Learning first appeared on Synced.

ai artificial intelligence bayesian bayesian deep learning deep deep learning laplace approximation learning machine learning machine learning & data science ml research study technology

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