Real industrial processes often present coupled static and dynamic characteristics, leading
to significant challenges for fault detection and isolation. However, traditional dynamic …

Correlation analysis is an invaluable tool in many domains, for better understanding data
and extracting salient insights. Most works to date focus on detecting high pairwise …

This paper introduces Tensor Visibility Graph-enhanced Attention Networks (TVGeAN), a
novel graph autoencoder model specifically designed for MTS learning tasks. The …

Correlation analysis is an invaluable tool in many domains, for better understanding the data
and extracting salient insights. Most works to date focus on detecting high pairwise …

Since the proposal of Granger causality, many researchers have followed the idea and
developed extensions to the original algorithm. The classic Granger causality test aims to …

Time series forecasting plays a crucial role in various real-world applications, such as
finance, energy, traffic, and healthcare, providing valuable insights for decision-making …

Most current data is multivariable, exploring and identifying valuable information in these
datasets has far-reaching impacts. In particular, discovering meaningful hidden association …

Mining on the spatio-temporal data based on network method, is advantage to explore the
dynamic changes of mobile communication system from a new perspective. The mobile …

摘要工业大数据已经成为我国制造业转型升级的重要战略资源, 工业大数据分析问题正引起重视
和关注. 时序数据作为工业大数据中一种重要的数据形式, 存在大量的数据质量问题 …

The similarity search task involves identifying pairs of similar vectors, eg, time series. For
example, given a query q, the user might wish to find all vectors in a dataset with a cosine …