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 ...
IEEE

Automated Spatial-Temporal Graph Neural Network Search for Skeleton-based Human Action Recognition on Edge Devices

Abstract: Graph neural networks (GNNs) have attracted significant attention in human action recognition (HAR) tasks due to their ability to model spatial-temporal relationships between body joints in ...
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 ...
C&EN

Efficient Learning of Molecular Properties Using Graph Neural Networks Enhanced with Chemistry Knowledge

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Graph neural networks (GNNs) have emerged as a powerful tool in predicting molecular ...
IEEE

Fast Adversarial Training for Graph Neural Network Based Resource Allocation

Abstract: In this letter, we propose a meta-learning-based fast adversarial training method to address the vulnerability of graph neural network (GNN) based resource allocation method to adversarial ...
Santa Clara University

HPC Machine Learning Tutorial

This tutorial is an adaptation of the NumPy Tutorial from Tensorflow.org. To run this tutorial, it is assumed that you already have access to the WAVE HPC with a user account and the ability to open a ...