IEEE

Deep Generative Models for Node Embedding and Neighborhood Prediction in Dynamic Graphs of Recommendation Systems

Abstract: In this article, we develop generative models that generate embeddings for graph nodes while using only their initial features without any knowledge about their neighborhoods and connections ...
IEEE

Weighted Graph Structure Learning with Attention Denoising for Node Classification

Abstract: The node classification in graphs aims to predict the categories of unlabeled nodes utilizing a small set of labeled nodes. However, weighted graphs often contain noisy edges and anomalous ...
GitHub

Survey of Graph Neural Network Models On DergiPark Scientific Article Dataset

Graph Convolutional Network (GCN), GraphSAGE, and Graph Attention Network (GAT) models are used in node classification and node clustering tasks. Variational graph autoencoder (VGAE) model is used in ...
GitHub

OGFormer:A Graph Transformer with Optimized Attention Scores for Node Classification

#Now that you're all here, don't forget to click on the little star.!!!!! #For quotes on function packages please refer to our article #We will follow up with the article "A Graph Transformer with ...