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Corruption is notoriously widespread in data collection, and has been widely studied through the introduction of various corruption models addressing specific cases. Motivated by the existence of a zoo of models, not yet well-related or compared to each other, we worked on a framework for unifying...

This page provides a brief summary of the course Bob will teach in Winter Semester 2024/25 at the University of Tübingen. The course is called Being a Scientist: Making Meaning by Making Science. Some content was previewed in the talk given at the IMPRS-IS bootcamp on 20 September 2024. ( slides) If...

The notion of a "style of reasoning" was developed by Ian Hacking, who explored in particular the statistical style of reasoning in XXX. In this project we build upon that work to analyse the style of reasoning of machine learning. We argue that (ironically) although ML makes great use of data, it...

Machine learning is mainly standing on the pillars of probability theory and statistics. It was Kolmogorov's celebrated book ``Grundbegriffe der Wahrscheinlichkeitsrechnung'' (translated as ''Foundations of the Theory of Probability'') which in 1933 laid the foundation for modern probability theory...

I am professor of foundations of machine learning systems at the University of Tübingen. I am a principal investigator in the Tübingen AI center and a member of the Cluster of Excellence Machine Learning in the Sciences. Current Research My current research is focused on a small number of basic...

Hello, I'm Rabanus. Since October 2021 I am pursuing my PhD under supervision of Bob Williamson in the group "Foundations of Machine Learning Systems". I am working on the implication of probability theoretical assumptions in machine learning and the quality of forecasts. As part of this endeavour I...