Research Center Machine Learning

About us

Informed Machine Learning Opens New Areas of Application

Informed Machine Learning (ML) combines state-of-the-art data-driven approaches with expert knowledge and simulation-based techniques. On the one hand, this provides reliable ML technology whose results are transparent and explainable. On the other hand, it opens up new application areas and makes it possible to learn even from limited data. Our researchers also investigate new ways of creating ML applications tailored to hardware and infrastructures as diverse as IoT devices, networked data centers, or quantum computers. In short, our activities focus on three main areas: Hybrid Learning, Simulation-based Learning and Resource Aware Learning.

The Research Center for Machine Learning bundles the competences of four Fraunhofer Institutes:

The Center for Machine Learning is part of the Fraunhofer Cluster Cognitive Internet Technologies, whose other partners are the centers for IoT-COMMS and Data Spaces.

Simulation-based Learning
Hybrid Learning
Resource Aware Learning