We develop principled AI methods to solve hard problems from the natural sciences. Our expertise are fundamental algorithms and their application to complex problems with spatial structure.
Geometric Machine Learning in Quantum Chemistry
Predicting molecular properties is important for a huge range of problems, from biochemistry to drug development.
The most universal approach to such predictions relies on quantum mechanics. We aim to dramatically speed up these quantum calculations using machine learning methods that respect the fundamental symmetries of the problem.
Home, Sweet Home
IWR is a central institute of our university, and a fantastic place where scientists from maths, CS, physics and more meet to develop methods that address some of the hardest problems out there.