IEEE

Semi-Supervised Learning With Graph Learning-Convolutional Networks

Abstract: Graph Convolutional Neural Networks (graph CNNs) have been widely used for graph data representation and semi-supervised learning tasks. However, existing graph CNNs generally use a fixed ...
Hackaday

Arduino Hacks

[ChrisN219] has an antique Coke machine that used to hold glass bottles. Now it holds around 30 tall boy cans of his favorite post-work suds. The only problem is that [Chris] has no idea how many cans ...
IEEE

Deep Learning for Dynamic Graphs: Models and Benchmarks

Abstract: Recent progress in research on deep graph networks (DGNs) has led to a maturation of the domain of learning on graphs. Despite the growth of this research field, there are still important ...
GitHub

VLLM with Supercluster Demo

This educational repository demonstrates the architectural principles and implementation techniques of high-performance Large Language Model (LLM) inference engines, from fundamental CUDA kernels to ...
GitHub

Microsoft Graph Training Module - Build Ruby on Rails apps with Microsoft Graph

This module will introduce you to working with Microsoft Graph to access data in Office 365 by building Ruby on Rails web applications. Lab - Build Ruby on Rails apps with Microsoft Graph In this lab ...