Much of our research applies AI and Machine Learning (see further below), but we are also interested in developing, improving or understanding Deep Learning or Statistical Learning/Modeling in general: How does it work? When does it fail? What can we do when data is scarce? Projects may involve re-implementing methods from the literature, systematic experiments with designed data sets, attempts at qualitative or performance improvements, etc. These projects generally require a background in Machine Learning.
These student projects can be started any time (including holidays) and can span over semester boundaries.
Remark: We are open for new proposals - if you are interested in Intelligent Music Processing, feel free to contact us!
Interpretable Machine Learning:
Machine Learning Theory: