Nowadays it is widely accepted that Artificial Intelligence (AI) is significantly influencing a
large number of domains, including railways. In this paper, we present a systematic literature …

Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …

In a short period of time, many areas of science have made a sharp transition towards data-
dependent methods. In some cases, this process has been enabled by simultaneous …

We have recently seen many successful applications of recurrent neural networks (RNNs)
on electronic medical records (EMRs), which contain histories of patients' diagnoses …

Without good models and the right tools to interpret them, data scientists risk making
decisions based on hidden biases, spurious correlations, and false generalizations. This …

Deep learning models for natural language processing (NLP) are increasingly adopted and
deployed by analysts without formal training in NLP or machine learning (ML). However, the …

Earth observation (EO) is increasingly used for map** and monitoring processes
occurring at the surface of Earth. Data acquired by satellites nowadays allow us to have a …

With the growing adoption of machine learning techniques, there is a surge of research
interest towards making machine learning systems more transparent and interpretable …

After Deep Learning (DL) regained popularity recently, the Artificial Intelligence (AI) or
Machine Learning (ML) field is undergoing rapid growth concerning research and real-world …

One of the challenges of Industry 4.0 is the creation of vertical networks that connect smart
production systems with design teams, suppliers, and the front office. To achieve such a …