ML2R – The Competence Center Machine Learning Rhine-Ruhr

The Competence Center Machine Learning Rhine-Ruhr is one of six national nodes for bringing the development of Artificial Intelligence and Machine Learning in Germany to a worldwide leading level. To this end, we establish cutting-edge research, support young scientists and strengthen technology transfer in companies.

We connect pioneering research institutions in Germany: the Technical University of Dortmund, the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS in Sankt Augustin, the Fraunhofer Institute for Material Flow and Logistics IML in Dortmund and the University of Bonn. The close integration of basic and application-oriented research builds the ideal foundation for innovation. In this way, we actively shape Germany’s future and contribute to securing the digital sovereignty of our country. Because Machine Learning is the key to intelligent products, new business models and a head start in international competition.

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Lights Out, Spot On: ML Blog Is Launched!

Discover exciting articles on Machine Learning and Artificial Intelligence in our ML blog. Learn first-hand what ML2R researchers are currently working on, find out about possible applications in practice and expand your knowledge!

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Main Areas of Research

Modular ML

In modular Machine Learning, systems are built up from individual modules and linked to existing methods in such a way that humans can use them intuitively and reuse them flexibly.

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ML with Restricted Resources

Machine Learning with restricted resources makes it possible to reliably perform calculations using Machine Learning even on small devices such as smartphones or directly in sensors.

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ML with Complex Knowledge

Machine Learning with complex knowledge integrates logical knowledge from various sources into learning systems to ensure reliable results even with small or insecure data sets.

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Human-oriented ML

Human-oriented Machine Learning places the human being at the center and designs Machine Learning procedures so that decisions become understandable, traceable and validatable for humans.

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