Welcome to Probabilistic Network Analysis


Description: Social networks, biological networks, sensor networks, the WWW, ... all are examples of networks that provide increasingly rich sources of data, and that become an increasingly important subject of study. The common underlying structure, and the similarity of  analysis tasks in very different domains concerned with networks has given rise to  the emergent discipline of network science. An important element of network science  consists of Machine Learning on graph data for network structure analysis and predictive  modeling. In this course core Machine Learning techniques for network data are presented.

The focus lies on techniques that build on probabilistic network models, and that apply statistical learning principles (however, some classical non-probabilistic approaches will also be discussed).

The scope of the course is (approximately) described by the following topics:

  • Random graph models; power laws;
  • Graph clustering/community detection
  • Node classification and link prediction
  • Random walk models: pagerank, hitting times, commute times
  • Multi-relational graphs and statistical relational learning


Prerequisites: Basic knowledge of probability theory and statistical inference. Ability to install and use a network analysis toolbox in the form of R or Matlab libraries.

Learning objectives: To understand basic principles and techniques of probabilistic network analysis. Ability to read current research papers applying probabilistic analysis techniques.

Organizer and lecturer: Associate Professor Manfred Jaeger, AAU, email: jaeger@cs.aau.dk

ECTS: 2.25

Time: 29, 30 May and 1 June 2017

Place: Selma Lagerløfs Vej 300, room 02.90

Zip code: 9220

City: Aalborg

Number of seats: 25

Deadline: 15 May 2017 


Important information concerning PhD courses We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.