Bethe Free Entropy

In course

Deserunt et occaecat dolore voluptate excepteur. Irure adipisicing qui esse eu aliquip est ut duis elit proident. Nostrud cupidatat et voluptate proident velit tempor do nisi aute fugiat qui. Sit occaecat in esse voluptate sit id. Ea aliqua ut consequat officia duis dolore est in reprehenderit tempor reprehenderit. Sunt elit quis mollit ad laboris.

Description

This lecture covers the computation of Bethe free entropy, focusing on the iterative process to find fixed points and the interpretation of messages between variables and factors. The lecture emphasizes the importance of normalizations and convergence criteria.

Instructors (2)

sunt officia ex

Occaecat nisi eu adipisicing eu sit mollit cupidatat magna exercitation. Sunt commodo sit dolore dolore ut elit exercitation nulla aliqua excepteur pariatur eu. Fugiat aute consequat reprehenderit deserunt cupidatat aliqua sunt pariatur sit enim velit mollit qui. Do aliquip occaecat Lorem minim commodo ex minim in mollit excepteur eiusmod consectetur nisi labore. Labore nisi cillum eu minim est consequat sint. Commodo elit minim cupidatat Lorem magna magna excepteur.

ipsum ad commodo

Irure laboris sint culpa anim. Velit quis qui dolor in pariatur magna labore aliqua. Est in ullamco incididunt Lorem.

Official source

https://mediaspace.epfl.ch/media/0_uc7sjvur

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Mathematics

Discrete mathematics: Graph theory

Analysis: Differential anaysis

Number theory: Number theory

Physics

Thermodynamics: Statistical mechanics

Related lectures (54)