no code implementations • 25 Oct 2023 • Ronald Schnitzer, Andreas Hapfelmeier, Sven Gaube, Sonja Zillner
In addition, to ensure the AI system's auditability, the proposed framework systematically documents evidence that the potential impact of identified AI hazards could be reduced to a tolerable level.
no code implementations • 23 Dec 2022 • Anna Himmelhuber, Dominik Dold, Stephan Grimm, Sonja Zillner, Thomas Runkler
Machine learning (ML) on graph-structured data has recently received deepened interest in the context of intrusion detection in the cybersecurity domain.
Decision Making Explainable Artificial Intelligence (XAI) +3
no code implementations • 3 Dec 2021 • Anna Himmelhuber, Stephan Grimm, Sonja Zillner, Mitchell Joblin, Martin Ringsquandl, Thomas Runkler
Similarly to other connectionist models, Graph Neural Networks (GNNs) lack transparency in their decision-making.
no code implementations • 25 Nov 2021 • Anna Himmelhuber, Stephan Grimm, Thomas Runkler, Sonja Zillner
The increasing importance of resource-efficient production entails that manufacturing companies have to create a more dynamic production environment, with flexible manufacturing machines and processes.
no code implementations • 17 Nov 2013 • Volker Tresp, Sonja Zillner, Maria J. Costa, Yi Huang, Alexander Cavallaro, Peter A. Fasching, Andre Reis, Martin Sedlmayr, Thomas Ganslandt, Klemens Budde, Carl Hinrichs, Danilo Schmidt, Philipp Daumke, Daniel Sonntag, Thomas Wittenberg, Patricia G. Oppelt, Denis Krompass
We argue that a science of a Clinical Data Intelligence is sensible in the context of a Big Data analysis, i. e., with data from many patients and with complete patient information.