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: Heterogeneous graph neural networks (HGNNs) have proven effective at capturing complex relationships in graphs with diverse node and edge types. However, centralized training in HGNNs raises ...

Instead of running Python scripts manually for routine tasks, why not automate them to run on their own, and at the time you want? Windows Task Scheduler lets you schedule tasks to run automatically ...

Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation In forecasting economic time series, statistical models often need to be complemented with a process to impose various ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Programming is a key transferable skill within the chemical sciences with applications ...

With the rise of microservices and distributed architectures, "event-driven" design has moved from niche to mainstream in the .NET world. At the heart of this trend is messaging -- the glue that lets ...

In this tutorial, we guide you through the development of an advanced Graph Agent framework, powered by the Google Gemini API. Our goal is to build intelligent, multi-step agents that execute tasks ...

In this tutorial, we demonstrate how to construct an automated Knowledge Graph (KG) pipeline using LangGraph and NetworkX. The pipeline simulates a sequence of intelligent agents that collaboratively ...

Welcome to the "three.js-visual-node-editor" repository! This is a visual graph editor designed specifically for Three TSL, allowing you to create and manipulate nodes easily for your Three.js ...