Real-world problems often exhibit complex relationships and dependencies, which can be
effectively captured by graph learning systems. Graph attention networks (GATs) have …

Automating the monitoring of industrial processes has the potential to enhance efficiency
and optimize quality by promptly detecting abnormal events and thus facilitating timely …

Although pre-trained transformers and reprogrammed text-based LLMs have shown strong
performance on time series tasks, the best-performing architectures vary widely across …

The rapid development of road traffic networks has provided a wealth of research data for
intelligent transportation systems. We are faced with vast high-dimensional traffic flow data …

With the increasing availability of multimodal educational data, there is a growing need to
effectively integrate and exploit multiple data sources to enhance student engagement …

Multivariate data analysis, as an important research topic in the field of machine learning,
focuses on how to utilize the intrinsic connection between feature variables and target …

Rotating machinery plays a vital role in the industrial sector, and ensuring its health status is
crucial for operational efficiency and safety. The construction of accurate health indicators …

Traffic crashes present substantial challenges to human safety and socio-economic
development in urban areas. Develo** a reliable and responsible traffic crash prediction …

Deep learning has been widely applied to automated leakage detection and location of
natural gas pipe networks. Prevalent deep learning approaches do not consider the spatial …

Electronic health records (EHRs) contain diverse patient information, including medical
notes, clinical events, and laboratory test results. Integrating this multimodal data can …