Deep neural networks (DNNs) have achieved state-of-the-art results in a broad range of
tasks, in particular the ones dealing with the perceptual data. However, full-scale application …

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 …

Large Language Models (LLMs) have gained widespread popularity due to their ability to
perform ad-hoc Natural Language Processing (NLP) tasks with a simple natural language …

State-of-the-art neural language models can now be used to solve ad-hoc language tasks
through zero-shot prompting without the need for supervised training. This approach has …

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 …

The use and creation of machine‐learning‐based solutions to solve problems or reduce
their computational costs are becoming increasingly widespread in many domains. Deep …

The rapid development of deep natural language processing (NLP) models for text
classification has led to an urgent need for a unified understanding of these models …

Advances in language modeling have led to the development of deep attention-based
models that are performant across a wide variety of natural language processing (NLP) …

Visual analytics systems integrate interactive visualizations and machine learning to enable
expert users to solve complex analysis tasks. Applications combine techniques from various …

Although deep learning models have been rapidly developed, their practical applications
still lag behind for building energy systems (BESs) fault diagnosis. Owing to the “black-box” …