Deep learning methods have made remarkable breakthroughs in machine general and automated driving (AD) particular. However, there are still unsolved problems to guarantee reliability safety of systems, especially effectively incorporate all available information knowledge the task. Knowledge graphs (KG) recently gained significant attention from both industry academia for applications that bene...

A foodshed is a geographic area from which a population derives its food supply, but a method to determine boundaries of foodsheds has not been formalized. Drawing on the food–water–energy nexus, we propose a formal network science definition of foodsheds by using data from virtual water flows, i.e., water that is virtually embedded in food. In particular, we use spectral graph partitioning for...

With multiple components and relations, financial data are often presented as graph data, since it could represent both the individual features complicated relations. Due to complexity volatility of market, constructed on is heterogeneous or time-varying, which imposes challenges modeling technology. Among technologies, neural network (GNN) models able handle complex structure achieve great per...

Abstract Community detection is a common task in social network analysis with applications variety of fields including medicine, criminology and business. Despite the popularity community detection, there no clear consensus on most effective methodology for signed networks. In this article, we summarize development networks evaluate current state-of-the-art techniques several real-world dataset...