Welcome to the 2017 summer school on graphical models. This will be the ninth in a series of summer school organized together with the Image Analysis and Computer Graphics section at DTU. The concept is to invite 2-4 internationally renowned experts to teach a week-long course together with local teachers from KU and DTU. The participants are a good mix of students from KU and DTU and international participants. The summer schools are held in remote locations to encourage interaction between students and teachers. In addition to bringing international expertise in to the groups, the summer schools also provide an important networking opportunity for the students.
- —-: Registration is binding
- July 1.: Registration deadline
- —-: Poster submission deadline
- August 14.-18.: Summer school
The summer school will consist of 5 days of lectures and exercises. The students will be expected to read a predefined set of scientific articles on graphical models prior to the course. Additionally, the students should bring a poster presenting their research field (preferably with an angle towards machine learning in image analysis).
The course will consist of the following parts:
- A crash course on the basics of graphical models.
- A theoretical insight in the challenges of graphical models.
- A practical session with hands-on exercises.
- Applications of graphical models in image analysis.
After participating in the summer school, the student should
- Understand graphical models and be able to differentiate between the different types of models.
- Have a strong knowledge about the theoretical foundations of graphical models learning
- Be able to implement basic graphical models from scratch and apply using appropriate model reduction techniques.
- Be able to apply graphical models for his/her own research projects.
Link to previous summer schools
- 2016 Summer school on semisupervised learning
- 2015 Convex and Discrete Optimization, Als
- 2014 Deep learning for image analysis, Langeland
- 2013 Tensors and Tensor Fields in Imaging
- 2012 Registration in Image Analysis and Computer Graphics, Falsterbo, Sweeden
- 2011 Graphs in Computer Graphics, Image and Signal Analysis, Bornholm
- 2010 Sparsity in Image and Signal Analysis, Iceland
- 2009 Manifold Learning in Image and Signal Analysis, Hven