| Foundations of Machine Learning | Lecturer |
Probabilistic Machine Learning (asynchronous videos, asymmetric (but synchronous) flipped classrooms, synchronous tutorials) | Hennig |
Statistical Machine Learning (asynchronous videos, tutorials/consultations via zoom) | Luxburg |
Diverse Topics in Machine Learning - Lectures | |
Machine Learning in Graphics and Vision ( asynchronous videos, synchronous Q&A via Zoom) | Geiger/Lensch |
Intelligent Systems and Computer Vision (lectures as videos, tutorials via Zoom (alternatively BBB)) | Stückler |
| Medical Data Science | Pfeifer |
| Neural Data Analysis | Berens |
| Mobile Robots | Zell |
| Advanced Statistics 2 | Gais |
Diverse Topics in Machine Learning - Seminars | |
| Explainable and Fair Machine Learning | Kasneci |
| Causality and Probability: A philosophical introduction for computer scientists | Spohn |
| Current Topics in Deep Neural Networks | Zell |
Current Trends in Deep Learning for Medicine | Berens |
| Advanced Topics in Computer Graphics and Computer Vision | Lensch |
Expanded Perspectives (just shown to highlight this seminar) | |
| The Ethics of Machine Learning | Grote |
