According to @godofprompt, graph databases offer superior efficiency for dynamic updates in AI-powered knowledge bases compared to traditional vector search methods. When using vector search, any ...

Introduction: Sleep disorders pose significant risks to patient safety, yet traditional polysomnography imposes substantial discomfort and laboratory constraints. We developed a non-invasive ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

Nigel Drego, Co-founder and Chief Technology Officer at Quadric, presented the “ONNX and Python to C++: State-of-the-art Graph Compilation” tutorial at this year’s Embedded Vision Summit. Quadric’s ...

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 ...

Introduction: Voxel hierarchy on dynamic brain graphs is produced by k-core percolation on functional dynamic amplitude correlation of resting-state fMRI. Methods: Directed graphs and their ...

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 ...

Abstract: Dynamic graph augmentation is used to improve the performance of dynamic GNNs. Most methods assume temporal locality, meaning that recent edges are more influential than earlier edges.

Abstract: Node classification on static graphs has achieved significant success, but achieving accurate node classification on dynamic graphs where node topology, attributes, and labels change over ...