marktechpost

Building a Multi-Node Graph-Based AI Agent Framework for Complex Task Automation

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 ...
EurekAlert!

D2-GCN: a graph convolutional network with dynamic disentanglement for node classification

Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...
GitHub

graph-editor-gui

Add a description, image, and links to the graph-editor-gui topic page so that developers can more easily learn about it.
Hacker

JavaScript JS0/JSSugar Proposals, Node.js 23, Next.js 15 RC2 and More - This Week in JS

We are a weekly podcast and newsletter made to deliver... Google’s proposal aims to split JavaScript into two parts: JS0, the core language that engines implement, and JSSugar, extra features that ...
IEEE

Deep Masked Graph Node Clustering

Abstract: In recent years, reconstructing features and learning node representations by graph autoencoders (GAE) have attracted much attention in deep graph node clustering. However, existing works ...
Frontiers

TP-GCL: graph contrastive learning from the tensor perspective

1 College of Computer, Qinghai Normal University, Xining, China 2 The State Key Laboratory of Tibetan Intelligent Information Processing and Application, Xining, China Graph Neural Networks (GNNs) ...
Oak Ridge National Lab

Attention-Augmented Parametric Kernel Graph Neural Network (APKGNN) for Node Classification

We present a new graph neural network, the Attention-based Parametric-Kernel augmented Graph Neural Network (APKGNN), developed for node classification tasks. Despite extensive work on modeling ...