HackerNoon

Building an Urban Heat Island Detector with Python, Satellite Data, and Machine Learning

Urban heat islands are a solvable data problem: this piece shows how to combine free satellite imagery, standard ...
KDnuggets

10 YouTube Channels Keeping You Ahead in AI

The artificial intelligence (AI) ecosystem is moving at a breakneck pace. If you try to read every new research paper on ArXiv or test every open-source repository that hits GitHub, you'll burn out ...
marktechpost

Using Graphify and NetworkX to Map Python Codebase Structure with God Nodes, Communities, and Architecture Visualizations

In this tutorial, we build a fully offline Graphify workflow that turns a realistic multi-module Python application into a knowledge graph. We start by installing Graphify and supporting graph ...
Network World

Ruckus Networks on the move again, this time acquired by Belden for $1.85 billion

Belden gains Wi-Fi and enterprise switching products in the deal and adds to its existing portfolio of passive networking infrastructure, OT wireless, and industrial switching gear. Belden (NYSE: BDC) ...
IEEE

Graph Neural Networks for Graphs With Heterophily: A Survey

Abstract: Recent years have witnessed fast developments of graph neural networks (GNNs) that have benefited myriad graph analytic tasks and applications. Most GNNs rely on the homophily assumption ...
XDA Developers

This self-hosted speed tracker monitors my network and graphs my internet's performance

Samir Makwana is a technology journalist and editor from India since past 18 years and his work appears on MakeUseOf, HowToGeek, GSMArena, BGR, GuidingTech, The Inquisitr, TechInAsia, TechWiser, and ...
science

Optical logic convolutional neural network

Optical computing presents a promising avenue to meet the escalating computational demands. However, optical analog computing is susceptible to environmental perturbations, relies heavily on ...
GitHub

scope3-gnn-mapper

scope3-gnn-mapper is an open-source Python framework that applies Graph Neural Networks (GNNs) to the Scope 3 supply chain emissions mapping challenge. Traditional Scope 3 accounting relies on ...
techxplore

New graph attention network models higher-order relationships in complex graph data

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
KDnuggets

5 Breakthroughs in Graph Neural Networks to Watch in 2026

One of the most powerful and rapidly evolving paradigms in deep learning is graph neural networks (GNNs). Unlike other deep neural network architectures, such as feed-forward networks or convolutional ...
IEEE

Contra Harmonic Mean Labeling of Some Graphs and Python-Based Continuous-Time Neural Networks for Solving the Travelling Salesman Problem in Artificial Intelligence

Abstract: In this paper, we prove Contra Harmonic Mean Labeling for some star related graphs such as $\mathrm{K}_{1, \mathrm{n}}, S(\mathrm{K}_{1, \mathrm{n ...