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Found 8 papers, 0 papers with code
AI Hazard Management: A framework for the systematic management of root causes for AI risks
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.
Detection, Explanation and Filtering of Cyber Attacks Combining Symbolic and Sub-Symbolic Methods
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
Combining Sub-Symbolic and Symbolic Methods for Explainability
Similarly to other connectionist models, Graph Neural Networks (GNNs) lack transparency in their decision-making.
Ontology-Based Skill Description Learning for Flexible Production Systems
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.
Towards a New Science of a Clinical Data Intelligence
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.
