Welcome to the website of research group
Theoretical Foundations of Artificial Intelligence
We work on the statistical theory of machine learning and deep learning. We provide mathematical understanding of learning algorithms, thereby establishing black-box AI tools as formal statistical principles.
We currently focus on the following topics.
- Statistical theory of unsupervised learning
- Theory of deep learning
- Machine learning on graphs
- Non-parametric methods for learning
We regularly offer lecture/seminars related to the theory of machine learning, including:
- Statistical foundations of learning (lecture, held every summer semester)
- Theoretical advances in deep learning (seminar, typically held every summer semester)
- Recent advances in theoretical machine learning (reading group, held throughtout the year and open for everyone)
We also supervise projects / theses on theoretical and applied machine learning. See here for recent projects.