Deep learning (DL) models have achieved impressive performance in various domains such
as medicine, finance, and autonomous vehicle systems with advances in computing power …

The need for interpretable and accountable intelligent systems grows along with the
prevalence of artificial intelligence (AI) applications used in everyday life. Explainable AI …

Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …

Visual analytics for machine learning has recently evolved as one of the most exciting areas
in the field of visualization. To better identify which research topics are promising and to …

The continuous advancement of Artificial Intelligence (AI) has been revolutionizing the
strategy of decision-making in different life domains. Regardless of this achievement, AI …

While deep learning models have achieved state-of-the-art accuracies for many prediction
tasks, understanding these models remains a challenge. Despite the recent interest in …

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 …

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 …

Understanding predictive models, in terms of interpreting and identifying actionable insights,
is a challenging task. Often the importance of a feature in a model is only a rough estimate …

We investigated the effects of example-based explanations for a machine learning classifier
on end users' appropriate trust. We explored the effects of spatial layout and visual …