Continual learning (CL) is a particular machine learning paradigm where the data
distribution and learning objective change through time, or where all the training data and …

This paper reviews the literature concerning technology used for creating and delivering
accessible museum and cultural heritage sites experiences. It highlights the importance of …

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a
driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted …

We analyze the knowledge acquired by AlphaZero, a neural network engine that learns
chess solely by playing against itself yet becomes capable of outperforming human chess …

A large set of the explainable Artificial Intelligence (XAI) literature is emerging on feature
relevance techniques to explain a deep neural network (DNN) output or explaining models …

Artificial Intelligence (AI) systems have made remarkable progress, attaining super-human
performance across various domains. This presents us with an opportunity to further human …

The use of artificial intelligence (AI) in a variety of research fields is speeding up multiple
digital revolutions, from shifting paradigms in healthcare, precision medicine and wearable …

Creative thinking skills are part of globalization era education and can be applied by
implementing innovative learning models. This study aims to test the effectiveness of the …

Classical machine learning algorithms often assume that the data are drawn iid from a
stationary probability distribution. Recently, continual learning emerged as a rapidly growing …

Ethics Guidelines for Trustworthy AI advocate for AI technology that is, among other things,
more inclusive. Explainable AI (XAI) aims at making state of the art opaque models more …