Embodied Artificial Intelligence This project focusses on different aspects of the sensori-motor loop in conjunction with information theory. The goal is to develop a mathematical understanding of how first principles of learning lead to cognitive capabilities.
Exponential Families & Information Maximization In this project the geometry of exponential families is studied from the perspective of information geometry and algebraic statistics. The results are of particular relevance in the context of learning theory.
Design of
Learning Systems
The goal of this project is to provide mathematical knowledge about various connectionistic models and to identify distinguished architectures of learning systems based on their expressive power and learning performance.
Robustness of
Functional Networks
The aim of this project is to develop a mathematical formalism of functional robustness and to demonstrate its utility in the context of biological networks.
Information Theory in
Causal Inference
This project studies how stochastic dependence is generated by causal interactions. It sets constraints on the underlying causal structure in terms of information-theoretic inequality relations.
Geometry & Complexity This project develops a geometric understanding of complexity. The aim of this approach is to relate various well-known concepts to each other.