Video/Webinars
Explainable AI for systems with functional safety requirements
Explainable AI (XAI) is vital for making AI decision-making processes transparent and understandable to human experts, and for ensuring safety and regulatory compliance.
Case studies
Application of the ALTAI tool to power grids, railway network and air traffic management
This document presents the responses from industry (operators of critical infrastructures) to the Assessment List for Trustworthy AI (ALTAI) questionnaire for three domains and specific use cases: power grid, railway network, and air traffic manag
White paper
Holistic framework for AI in critical network infrastructures
This document establishes the main foundations of the AI4REALNET project, in particular, the following key outcomes: - The formal specification of domain-specific use cases (UCs), replicating real-world operating scenarios involving human operator
Video/Webinars
Towards functional safety management for AI-based critical systems
The webinar provides attendees with a comprehensive understanding of the challenges and opportunities associated with integrating AI into safety-critical systems.
Software resources
Decentralized-gnn
A package for implementing and simulating decentralized Graph Neural Network algorithms for classification of peer-to-peer nodes.
Software resources
PandA: Unsupervised learning of parts and appearances in the feature maps of GANs
We propose an architecture-agnostic approach that jointly discovers factors representing spatial parts and their appearances in an entirely unsupervised fashion.