Abstract 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 …

In recent years, many accurate decision support systems have been constructed as black
boxes, that is as systems that hide their internal logic to the user. This lack of explanation …

Explainable artificial intelligence is an emerging research direction helping the user or
developer of machine learning models understand why models behave the way they do …

A substantial amount of research has been carried out in Explainable Artificial Intelligence
(XAI) models, especially in those which explain the deep architectures of neural networks. A …

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 …

The increase in spatiotemporal resolution of neuroimaging devices is accompanied by a
trend towards more powerful multivariate analysis methods. Often it is desired to interpret the …

Abstract Machine learning (ML) techniques such as (deep) artificial neural networks (DNN)
are solving very successfully a plethora of tasks and provide new predictive models for …

Machine learning techniques are increasingly gaining attention due to their widespread use
in various disciplines across academia and industry. Despite their tremendous success …

Abstract Machine learning is a powerful tool for creating computational models relating brain
function to behavior, and its use is becoming widespread in neuroscience. However, these …

As the big data generated by the development of modern experiments and computing
technology becomes more and more accessible, the material design method based on …