Course List for the Summersemester 2021

Foundations of Machine Learning	Lecturer
Probabilistic Machine Learning	Hennig
Statistical Machine Learning	Hein
Diverse Topics in Machine Learning - Lectures
Computer Vision	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
Machine Learning for and with Dynamical Systems	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: