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 ...

This repository is the official implementation of "DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models" accepted by the Main Technical Track of the 39th ...

Modern business intelligence demands speed, and utilizing AI tools for Excel is the ultimate way to hyper-charge your data workflows this year.

Abstract: Understanding the underlying graph structure of a nonlinear map over a particular domain is essential in evaluating its potential for real applications. In this paper, we investigate the ...

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, ...

A campaign active since last November has been targeting Python developers building Telegram bots with trojanized Pyrogram ...

Organic traffic is down, but one marketer says revenue is up. This AEO dissection unpacks why fewer site visits might mean ...

New benchmarks show semantic code graphs helping coding agents find change locations faster and complete updates more ...

Data analysis is no longer a specialist skill reserved for analysts. It now supports finance, trading, ecommerce, marketing, ...

Every Python developer knows some or all of these libraries, because they’re stable, reliable, and excellent at what they do.