The past decade has witnessed a plethora of works that leverage the power of visualization
(VIS) to interpret machine learning (ML) models. The corresponding research topic, VIS4ML …

Over the past years, an increasing number of publications in information visualization,
especially within the field of visual analytics, have mentioned the term “embedding” when …

In recent years, visual analytics (VA) has shown promise in alleviating the challenges of
interpreting black-box deep learning (DL) models. While the focus of VA for explainable DL …

As applications of generative AI become mainstream, it is important to understand what
generative models are capable of producing, and the extent to which one can predictably …

While deep generative models (DGMs) have gained popularity, their susceptibility to biases
and other inefficiencies that lead to undesirable outcomes remains an issue. With their …