STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

Abstract: Graph Neural Networks (GNNs), which obtain node embeddings by attribute propagates along graph topology, exhibit significant power in graph-structured data mining. However, graphs in the ...

What if you could transform vast amounts of unstructured text into a living, breathing map of knowledge—one that not only organizes information but reveals hidden connections you never knew existed?

WARSAW, May 20 (Reuters) - Polish authorities have indicted a man charged with planning to help Russian foreign intelligence services prepare a possible attempt to assassinate Ukraine's president, ...

Abstract: Text-graph convolutional Network (TextGCN) is the fundamental work representing corpus with heterogeneous text graphs. Its innovative application of GCNs for text classification has garnered ...

Some people use their Macs to drive enormous HDTVs, letting them access a wide range of audio and video apps on a Mac and streaming video services while also retaining the security of the Mac ...

Jupyter Notebooks are a powerful open-source tool that allows users to create and share documents that contain live code, equations, visualizations, and narrative text. They are widely used in data ...

WASHINGTON, Oct 22 (Reuters) - The European Central Bank needs to improve how it communicates policy intentions and uncertainty, but copying the U.S. Federal Reserve's "dot plot" projection method is ...