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David Reeb

Research Scientist

 David Reeb

About Me

In my research at the Bosch Center for Artificial Intelligence, I aim to contribute to a deeper and mathematically rigorous understanding of machine learning methods. My main interest lies in the generalization performance of learning algorithms, in particular for the case of limited sample size and noisy data which is relevant to the real world.

I am fond of Bayesian methods and currently applying them to problems in the automotive domain. Prior to Bosch, I worked as a postdoctoral researcher in the Quantum Information sciences, employing methods from Mathematical Physics and optimization.

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My Research Fields

  • Statistical Learning Theory
  • Gaussian Processes
  • Probabilistic Modelling
  • Convex Optimization