The application of Artificial Intelligence (AI) across a wide range of domains comes with both
high expectations of its benefits and dire predictions of misuse. While AI systems have …

Most machine learning algorithms are configured by a set of hyperparameters whose values
must be carefully chosen and which often considerably impact performance. To avoid a time …

Modern approach to artificial intelligence (AI) aims to design algorithms that learn directly
from data. This approach has achieved impressive results and has contributed significantly …

The spread of AI-embedded systems involved in human decision making makes studying
human trust in these systems critical. However, empirically investigating trust is challenging …

Artificial Intelligent (AI) and Machine Learning (ML) algorithms are coming out of research
labs into the real-world applications, and recent research has focused a lot on Human-AI …

In the last few years, electron microscopy has experienced a new methodological paradigm
aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine …

Artificial intelligence (AI) technology has been increasingly used in the implementation of
advanced Clinical Decision Support Systems (CDSS). Research demonstrated the potential …

After Deep Learning (DL) regained popularity recently, the Artificial Intelligence (AI) or
Machine Learning (ML) field is undergoing rapid growth concerning research and real-world …

Trust is a crucial factor for the adoption and responsible usage of generative AI tools in
complex tasks such as software engineering. However, we have a limited understanding of …

Generative machine learning models have recently been applied to source code, for use
cases including translating code between programming languages, creating documentation …