Graph machine-learning (ML) methods have recently attracted great attention and have
made significant progress in graph applications. To date, most graph ML approaches have …

Advances in artificial intelligence (AI), especially deep learning (DL), have facilitated
magnetic resonance imaging (MRI) data analysis, enabling AI-assisted medical image …

Machine learning (ML) and deep learning (DL), in particular, are common tools for anomaly
detection (AD). With the rapid increase in the number of Internet-connected devices, the …

Federated Learning (FL) can combine multiple clients for training and keep client data local,
which is a good way to protect data privacy. There are many excellent FL algorithms …

Accurate identification of potential drug–target interactions (DTIs) is a crucial task in drug
development and repositioning. Despite the remarkable progress achieved in recent years …

Sign language recognition has been utilized in human–machine interactions, improving the
lives of people with speech impairments or who rely on nonverbal instructions. Thanks to its …

As a convenient, economical, and eco-friendly travel mode, bike-sharing greatly improved
urban mobility. However, it is often very difficult to achieve a balanced utilization of shared …

Task fMRI provides an opportunity to analyze the working mechanisms of the human brain
during specific experimental paradigms. Deep learning models have increasingly been …

Federated learning is an emerging technology that enables the decentralised training of
machine learning-based methods for medical image analysis across multiple sites while …

Anisotropy in crystals plays a pivotal role in many technological applications. For example,
anisotropic electronic and thermal transport are thought to be beneficial for thermoelectric …