While graph machine learning, and notably graph neural networks (GNNs), have gained immense traction in recent years, application is predicated on access to a known input graph upon which predictive ...

The goal is to learn the network characteristics and disease dynamics of the pandemic occurred in Sweden during 2009, commonly known as swine flu. As a secondary goal, we develop an algorithm to ...

Abstract: Graph-based data are very ubiquitous in many real-world scenarios, and it is usually difficult to mine valuable information from the large scale graphs because of traditional sparse and high ...

Abstract: Depth information is being widely used in many real-world applications. However, due to the limitation of depth sensing technology, the captured depth map in practice usually has much lower ...