Abstract: Graph neural networks (GNNs) have demonstrated significant success in solving real-world problems using both static and dynamic graph data. While static graphs remain constant, dynamic ...

To some, METR’s “time horizon plot” indicates that AI utopia—or apocalypse—is close at hand. The truth is more complicated. MIT Technology Review Explains: Let our writers untangle the complex, messy ...

This repository contains the official PyTorch implementation and the UMC4/12 Dataset for the paper: [UrbanGraph: Physics-Informed Spatio-Temporal Dynamic Heterogeneous Graphs for Urban Microclimate ...

A software engineer and book author with many years of experience, I have dedicated my career to the art of automation. A software engineer and book author with many years of experience, I have ...

In our world of today, spreadsheets function mainly as a means to provide quick and easy plotting methods for numerical data in various kinds of graphical charts. Graphs provide us with an effective ...

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 ...

Lucas is a writer and narrative designer from Argentina with over 15 years of experience writing for games and news. He keeps a watchful eye at the gaming world and loves to write about the hottest ...