Counterfactual explanations (CFEs) are a popular approach in explainable...
Employee attrition is an important and complex problem that can directly...
In modern business processes, the amount of data collected has increased...
Counterfactual explanations are a popular type of explanation for making...
The phenomena of concept drift refers to a change of the data distributi...
We investigate the task of missing value estimation in graphs as given b...
Machine learning based decision making systems applied in safety critica...
Dimensionality reduction is a popular preprocessing and a widely used to...
Transparency is a major requirement of modern AI based decision making
s...
The application of machine learning based decision making systems in saf...
The notion of concept drift refers to the phenomenon that the data gener...
Counterfactual explanations (CFEs) highlight what changes to a model's i...
To foster usefulness and accountability of machine learning (ML), it is
...
Water distribution networks are a key component of modern infrastructure...
While machine learning models are usually assumed to always output a
pre...
Transparency is an essential requirement of machine learning based decis...
Many decision making systems deployed in the real world are not static -...
Fairness and explainability are two important and closely related
requir...
With the increasing deployment of machine learning systems in practice,
...
The increasing deployment of machine learning as well as legal regulatio...
The notion of drift refers to the phenomenon that the distribution, whic...
Due to the increasing use of machine learning in practice it becomes mor...
With the increasing use of machine learning in practice and because of l...