Digicampus
Lecture: Bayesian Networks - Details
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Lehrveranstaltung wird in Präsenz abgehalten.

General information

Course name Lecture: Bayesian Networks
Course number INF-0088, INF-0263
Semester SS 2023
Current number of participants 84
Home institute Multimedia und maschinelles Sehen
Courses type Lecture in category Teaching
First date Tue., 18.04.2023 12:15 - 13:45, Room: (1058 N)
Online/Digitale Veranstaltung Veranstaltung wird in Präsenz abgehalten.
Hauptunterrichtssprache deutsch

Course location / Course dates

(1058 N) Tuesday: 12:15 - 13:45, weekly (12x)
(Nur Online Video "BN_7_Approximate_Inference.mp4"; keine physische Vorlesung) Tuesday: 12:15 - 13:45, weekly (1x)

Module assignments

Comment/Description

Probability theory is a powerful tool for inferring the value of missing variables given a set of other variables. As the number of variables in a system increases, the joint probability distribution over these variables becomes overwhelmingly large. In this lecture we examine the implications of factoring one large joint probability distribution into a set of smaller conditional distributions by exploiting independencies between variables and study suitable algorithms for inference.