We typically organize and teach the following courses:

  • Game Physics (IN0037) – this course gives a basic introduction into numerical simulations for physics simulations. It targets Lagrangian methods such as mass-spring systems, rigid bodies, and particle-based liquids. (WS, Bachelor)
  • Advanced Deep Learning for Physics (IN2298) – this course is a follow up to “Game Physics” (formerly under the name “Deep Learning and Numerical Simulations”). It extends the simulations to more accurate Eulerian methods, and explains how to combine them with state-of-the-art deep learning techniques (convolutional neural networks, in particular). (SS, Master)
  • Computer Games Laboratory – this is a practical course to develop full game projects within smaller teams. The projects follow a milestone-based development process over the course of the semester. You can find a list of game projects here. (WS & SS, Games Engineering Master)
  • Seminar Deep Learning in Computer Graphics – this seminar covers recent developments and research topics from the area of deep learning techniques in the area of computer graphics. (WS & SS, Bachelor / Master)

We are part of the organisational unit “I15” in Informatics. Thus, all our lectures and seminars are listed there. Below you can find links to the individual summer / winter semesters.