Repository · GitHub

JavierAntoran/Bayesian-Neural-Networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

View on GitHubReport an issue

Owner	JavierAntoran
License (as declared)	MIT
Stars	1,976
Forks	306
Main language	Jupyter Notebook
Created	11 March 2019
Last updated at source	20 October 2023

jupyter notebookapproximate-inferencebayes-by-backpropbayesian-inferencebayesian-neural-networksclassificationdeep-learninghmckronecker-factored-approximationlangevin-dynamicslocal-reparametrization-trickmc-dropoutmcmcout-of-distribution-detectionpytorchregressionreproducible-researchsglduncertaintyuncertainty-neural-networksvariational-inference

Embed this entry

<iframe src="https://silytics.si/embed/item/9674e470-46ef-45bb-98bf-574282a76dd3" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from GitHub and links to the original. Information may be incomplete or out of date. Last refreshed 15 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.