Publications

Recent Preprints and Papers

Gaussian processes scale prohibitively with the size of the dataset. In response, many approximation methods have been developed, which …

Gaussian process hyperparameter optimization requires linear solves with, and log-determinants of, large kernel matrices. Iterative …

Linear systems are the bedrock of virtually all numerical computation. Machine learning poses specific challenges for the solution of …

Many applications of classification methods not only require high accuracy but also reliable estimation of predictive uncertainty. …

Talks

Recent and Upcoming

Projects

Software, Tech Reports, etc.

Probabilistic Numerics (PN) interprets classic numerical routines as inference procedures by taking a probabilistic viewpoint. This …

Accurate representation of uncertainty in classification problems can be as critical as high prediction accuracy in computer vision, …

In this project we analyzed time-optimal control problems with linear dynamics and numerical methods for solving them. When …

Contact

  • University of Tübingen
    AI Research Building
    Maria-von-Linden-Str. 6
    72076 Tübingen / Germany
  • Office hours by appointment