Scientific Machine Learning
Machine Learning is a key innovation of the last two centuries with the potential to transform societies across the globe.
Goals and Perspectives
At Heidelberg University, the major aims of researchers involved in the field are
- Driving fundamental research into the understanding of current and future machine learning
- Using machine learning to enable the solution of long-standing problems in the sciences
- Studying the impact of machine learning on society.
Our science-based approach to machine learning, and our use of machine learning to solve important problems in the sciences, is summarized by our motto “Scientific Machine Learning”.
Within the university, scientific machine learning plays a central role in the activities of the STRUCTURES Cluster of Excellence, which aims at pushing the limits of foundational research, and at the Interdisciplinary Center for Scientific Computing (IWR), which enables applications in the natural and life sciences, the engineering sciences, as well as the humanities.
The Faculties of Mathematics and Computer Science, Physics and Astronomy, Engineering Sciences, Biosciences and Medicine will further advance scientific machine learning with seven new professorships that will be established in the field by 2028.
Heidelberg University Part of ELIZA Konrad Zuse School of Excellence in Artificial Intelligence
MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images
Machine Learning Talks on Campus
Machine Learning Talks on Campus is an information service about talks, workshops and other events in the local community.