Given the pressing need for assuring algorithmic transparency, Explainable AI (XAI) has
emerged as one of the key areas of AI research. In this paper, we develop a novel Bayesian …

Recently, artificial intelligence and machine learning in general have demonstrated
remarkable performances in many tasks, from image processing to natural language …

Artificial Intelligence (AI) is becoming fundamental in almost all activity sectors in our society.
However, most of the modern AI techniques (eg, Machine Learning–ML) have a black box …

The development of “intelligent” systems that can take decisions and perform autonomously
might lead to faster and more consistent decisions. A limiting factor for a broader adoption of …

Abstract Although Deep Neural Networks (DNNs) have great generalization and prediction
capabilities, their functioning does not allow a detailed explanation of their behavior …

Machine and deep learning have proven their utility to generate data-driven models with
high accuracy and precision. However, their non-linear, complex structures are often difficult …

Deep learning has made significant contribution to the recent progress in artificial
intelligence. In comparison to traditional machine learning methods such as decision trees …

At the dawn of the fourth industrial revolution, we are witnessing a fast and widespread
adoption of artificial intelligence (AI) in our daily life, which contributes to accelerating the …

When it comes to complex machine learning models, commonly referred to as black boxes,
understanding the underlying decision making process is crucial for domains such as …

Currently, explainability represents a major barrier that Artificial Intelligence (AI) is facing in
regard to its practical implementation in various application domains. To combat the lack of …