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) and on YouTube (video email alert).
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.