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.
Software resources
Decentralized-gnn
A package for implementing and simulating decentralized Graph Neural Network algorithms for classification of peer-to-peer nodes.
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
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.
Software resources
pygrank
pygrank is an open source framework to define, run and evaluate node ranking algorithms.