Course List for the Summersemester 2021
| Foundations of Machine Learning | Lecturer |
Hennig | |
| Hein | |
Diverse Topics in Machine Learning - Lectures | |
| Geiger | |
| Advanced Probabilistic methods for Machine Learning and Applications | De Bacco |
| Machine Learning Approaches in Climate Science | Goswami |
| Neural Data Analysis | Berens |
| Mobile Robots | Zell |
| Introduction to Formal Epistemology and Ranking Theory in Particular | Spohn |
| Efficient Machine Learning in Hardware | Bringmann |
| Artificial Neural Networks II - “Recurrent and Generative Artificial Neural Networks” | Butz |
| Data Compression with Deep Probabilistic Methods | Bamler |
Diverse Topics in Machine Learning - Seminars | |
| Machine Learning for Health | Pfeifer |
| Machine Learning Methods for Scientific Discovery | Macke |
| Machine Learning and Artificial Neural Networks in Biomedical Applications | Nagel |
Hennig | |
| Fairness in Machine Learning | Samadi, Grote, Hennig |
| Advanced Topics in Data Science and Analytics : Explainable and Fair Analytics | Kasneci |
| Deep Learning for Vision and Graphics | Pons Moll |
Previous semesters: