Methods and Algorithms
To solve complex real-world tasks we develop machine learning solutions using state-of-the-art supervised Deep Learning methods as well as self-supervised approaches and evaluate their quality along different quality dimensions.
AI in Medicine and the Sciences
Central application areas of our research lie in medicine and the Sciences, where we develop solutions for real-world problems involving different data modalities. Together with practitioners and other users we always strive for developing the best solutions.
Machine Learning for Climate Change
Climate change research is a vast and significantly important research topic. Together with partners from our research network we strive for developing machine learning-based methods that can be helpful to push further research developments in this field.