In this work, we focus on robust time series representation learning. Ou...
Passenger clustering based on travel records is essential for transporta...
This paper proposes the Spatio-Temporal Crowdedness Inference Model (STC...
Correlated time series analysis plays an important role in many real-wor...
This paper proposes to learn Multi-task, Multi-modal Direct Acyclic Grap...
Data imputation is a prevalent and important task due to the ubiquitousn...
Graph alignment, which aims at identifying corresponding entities across...
Graph neural networks (GNNs) are popular weapons for modeling relational...
Graph self-supervised learning has been vastly employed to learn
represe...
As the complexity of production processes increases, the diversity of da...
Spatiotemporal data is very common in many applications, such as
manufac...
Low-rank tensor decomposition and completion have attracted significant
...
This article develops a method to construct the optimal sequential test ...