Graphical models form a cornerstone of modern data analysis by providing a visually intuitive framework to represent and reason about the complex interdependencies among variables. In particular ...

Topics include directed and undirected graphical models, exact and approximate inference methods, and supervised and unsupervised parameter and structure learning. Grades: Homework will involve both ...

This courses introduces causal inference methods, primarily using probabilistic graphical models, to identify and estimate counterfactual quantities as functions of observational data. We will discuss ...

M.Sc. Kari Rantanen defends his doctoral thesis Optimization Algorithms for Learning Graphical Model Structures on Wednesday the 8th of December 2021 at 15 o'clock through remote access.His opponent ...

A five-minute formula from Alexander Denev that takes you through a simple probabilistic graphical model and explains how and why these are used. Find out more about the ground-breaking book, ...