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 ...
Overview: Learn the 10 most frequently asked data visualization interview questions along with practical sample answers.Understand what recruiters expect ...
Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...
This project demonstrates a comprehensive data warehousing and analytics solution, from building a data warehouse to generating actionable insights. Designed as a portfolio project, it highlights ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Abstract: Knowledge Graphs (KGs) have recently emerged as a powerful tool for extracting directed multi-relational "knowledge" from structured facts within massive urban mobility data, supporting ...
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