Machine learning plays a role in many deployed decision systems, often in ways that are
difficult or impossible to understand by human stakeholders. Explaining, in a human …

It is important to manage operational disruptions to ensure the success of supply chain
operations. To achieve this aim, researchers have developed techniques that determine the …

The question of molecular similarity is core in cheminformatics and is usually assessed via a
pairwise comparison based on vectors of properties or molecular fingerprints. We recently …

Many of today's decision making systems deployed in the real world are not static—they are
changing and adapting over time, a phenomenon known as model adaptation takes place …

Explanations for Convolutional Neural Networks (CNNs) based on relevance of input pixels
might be too unspecific to evaluate which and how input features impact model decisions …

In recent years, various machine and deep learning architectures have been successfully
introduced to the field of predictive process analytics. Nevertheless, the inherent opacity of …

As a popular approach in Explainable AI (XAI), an increasing number of counterfactual
explanation algorithms have been proposed in the context of making machine learning …

Operational disruptions have a profound negative impact on supply chain companies'
business and financial performance. These companies counter such disruptions by …

Deep learning has been extensively utilized in the domains of bioinformatics and
chemoinformatics, yielding compelling results. However, neural networks have …