Probabilistic ML - Lecture 16 - Graphical Models
Channel: Tübingen Machine Learning
Date: 12/06/2020

This is the sixteenth lecture in the Probabilistic ML class of Prof. Dr. Philipp Hennig in the Summer Term 2020 at the University of Tübingen. 

Time-stamped slides available at https://uni-tuebingen.de/en/180804.

Contents: 
* Directed Graphical Models / Bayesian Networks
* Plate notation
* Markov Random Fields
* d-Separation
* Markov Blankets
* Hammersley-Clifford Theorem

© Philipp Hennig / University of Tübingen, 2020 CC BY-NC-SA 3.0