Source: arXiv AI Papers
The STM-Graph framework offers a modular approach to handling the complexities of urban spatio-temporal data. By integrating various spatial mapping methods and urban features from OpenStreetMap, it simplifies the process of data representation for predictive analytics.
Moreover, the incorporation of multiple GNN models within the framework allows for diverse applications in urban computing. With visualization tools and a user-friendly graphical interface, this framework promotes rapid experimentation, benchmarking, and the integration of new methods and models, ultimately supporting researchers and industry practitioners alike.
👉 Pročitaj original: arXiv AI Papers
