Independent Research Groups
Autonomous Vision

Max Planck Research Group for Autonomous Vision

We are interested in computer vision and machine learning with a focus on 3D scene understanding, parsing, reconstruction, material and motion estimation for autonomous intelligent systems such as self-driving cars or household robots. In particular, we investigate how complex prior knowledge can be incorporated into computer vision algorithms for making them robust to variations in our complex 3D world. You can follow us on GoogleScholar (paper email alert), on YouTube (video email alert) and on Facebook. Pictures from recent group activities can be found in our gallery!

Probabilistic Numerics

The Independent Max Planck Research Group on Probabilistic Numerics

Numerical Problems --- linear algebra and optimization, integration and the solution of differential equations --- are the computational bottleneck of artificial intelligent systems. Intriguingly, the numerical algorithms used for these tasks are also compact little intelligent agents themselves. They estimate unknown / uncomputable quantities by observing the result of feasible computations. They also actively decide which computations to perform. 

The Research Group on Probabilistic Numerics studies this philosophical and mathematical connection between computation and inference. We aim to build a theoretical understanding of numerical computer algorithms as agents acting rationally under uncertainty. We analyse existing algorithms from this viewpoint, and propose novel algorithms that provide functionality for key computational challenges in the science of Intelligent Systems.

Logo of the Emmy Noether ProgrammeFrom early 2015 until late 2016, our work was kindly supported by a grant in the Emmy Noether Programme of the DFG. From Dezember 2016, the group is principally funded by the Max Planck Society.

Statistical Learning Theory

Max Planck Fellow Group

We work on the theoretical analysis of machine learning algorithms. Our current focus is on comparison-based learning algorithms and on algorithms on random graphs and networks. The group is lead by Ulrike von Luxburg, the funding comes from a Max Planck Fellowship.

The groups by Ulrike von Luxburg are distributed between the Max Planck Institue and the University of Tübingen, our main webpage is the one at the university .

The Max Planck branch of our group consists of the following people: