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 targets combinations of physical simulations and deep learning methods. (Note: it formerly had the name “Deep Learning and Numerical Simulations”). It covers some more advanced simulation methods, and explains how to combine them with state-of-the-art deep learning techniques (differentiable physics solvers, 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)
- Seminars: Deep Learning in Computer Graphics and Deep Learning in Physics – these seminars cover recent developments and research topics from the area of deep learning techniques in the area of computer graphics and physics. (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.
- Teaching for WS 2022/23
- Teaching for SS 2022
- Teaching for WS 2021/22
- Teaching for SS 2021
- Teaching for WS 2020/21
Or you can view the current list in TUM-online.