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:
- Institute for Intelligent Analysis and Information Systems IAIS (lead)
- Institute of Optronics, System Technologies and Image Exploitation IOSB
- Institute for Industrial Mathematics ITWM
- Institute for Algorithms and Scientific Computing SCAI
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.