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
Article/Books/eBooks
Uncertainty-Based Learning of a Lightweight Model for Multimodal Emotion Recognition
In this paper, the authors propose a lightweight neural network architecture that extracts and performs the analysis of multimodal information using the same audio and visual networks across multiple temporal segments.
White paper
Position paper on AI for the operation of critical energy and mobility network infrastructures
This position paper outlines AI4REALNET’s approach to applying AI in network infrastructure operations, translating application needs into algorithmic proposals for effective human-AI collaboration in decision-making processes.
Software resources
CO2A – Contrastive Conditional domain Alignment
A novel unsupervised domain adaptation approach for action recognition from videos, inspired by recent literature on contrastive learning.
Software resources
pygrank
pygrank is an open source framework to define, run and evaluate node ranking algorithms.
Software resources
InDistill
InDistill enchances the effectiveness of the Knowledge Distillation procedure by leveraging the properties of channel pruning to both reduce the capacity gap between the models and retain the information geometry.