Deep Learning Techniques: Wetraining.develop inductive biases to increase generalisation capabilities of deep neural networks. Particularly, we invent methods which induce and exploit structure of the data, the model and
Explainable AI: We develop novel techniques for explaining how self-learning AI systems (like Deep Neural Networks) perform their tasks. We particularly focus on providing explanations that are understandable for non-experts while still being faithful. We use established methodology and models from neuroscience and adapt them to build and understand AI systems.
|Audio-Processing: Speech, Music Information Retrieval:|
|Medical Imaging: We rethink medical image processing algorithms to improve diagnosis of patients. We focus especially on the refinement of x-ray image styles and their quality.|
|Education: We research on how technology can enhance the learning experience and rethink the way we educate our students about AI.|