Teaching
Summer term 2023
Practical course on applying deep learning for image generation.
Winter term 2022/2023
Seminar where recent deep learning papers are presented and discussed.
Summer term 2022
Seminar where recent computational neuroscience papers are presented and discussed.
Practical course on applying deep learning for image generation.
Bachelor’s and Master’s theses
General requirements
We expect prospective students to have substantial knowledge in machine learning, its mathematical foundations and Python programming. We therefore strongly recommend that students interested in doing their thesis in our lab should take our courses on Machine Learning, Deep Learning and took the Fachpraktikum Data Science. Exceptions are possible if well motivated.
Further recommended lectures are:
- M.Inf.2201: Probabilistic Machine Learning (by Fabian Sinz)
- B.Inf.1231: Infrastructures for Data Science (by Philipp Wieder)
- M.WIWI-QMW.0002: Advanced Statistical Inference (by Elisabeth Bergherr)
Please note, our thesis supervision capacity is limited and we receive more thesis inquiries than we are able supervise. Therefore, we have to select candidates. If you are interested, please write an email with the subject “Master’s thesis” or “Bachelor’s thesis” containing one to three sentences about what you would like to work on and your study record to the supervisor stated below.
We will get back to you within a few days. Otherwise, do not hesitate to remind us :).
