Students gave their consent that their stories could be used for research purposes and might be published. Out of a class of ...

Conventional time series models are restricted to narrow historical data patterns, missing out on product metadata, ...

Anomaly detection in multivariate time series (MTS) is crucial in domains such as industrial monitoring, cybersecurity, healthcare, and autonomous driving. Deep learning approaches have improved ...

A research team led by Prof. Li Hai from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has developed a novel deep learning framework that significantly improves the ...

Classification models for multivariate time series have drawn the interest of many researchers to the field with the objective of developing accurate and efficient models. However, limited research ...