This project examines the performance of several Graph Neural Network (GNN) versions, such as Graph Autoencoders, Graph Convolutional Networks, Graph Attention Networks, and Graph Sample and ...
Sreesankar10/Analyzing-GNN-Models-for-Community-Detection-Using-Graph-Embeddings-A-Comparative-Study
This project focuses on the comparative analysis of Graph Neural Networks (GNNs) and traditional clustering algorithms for graph-structured data analysis. GNNs have emerged as powerful tools for ...
Abstract: Recent studies on integrating multiple omics data highlighted the potential to advance our understanding of the cancer disease process. Computational models based on graph neural networks ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results