Socio-economic data with fine-grained spatial resolution forms the basis of socio-spatial analysis and policymaking. In response to the limited availability of such data in China, this study provides ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Machine learning techniques have emerged as a useful tool for identifying complex patterns and correlations in large datasets, such as associating catalyst performance to its physicochemical ...