Graph Embedding Evaluation / Code and Datasets for "Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations" (Bioinformatics 2020)

GPU implementation of GCN (Graph Convolutional Networks)

Code for both the IEEE Big Data 2017 Paper: Evaluating the quality of graph embeddings via topological feature reconstruction and the Springer Data Science and Engineering paper: Exploring the Semantic Content of Unsupervised Graph Embeddings: An Empirical Study

Welcome to the Graph Mining (06837-01) class repository for the Department of Artificial Intelligence at the Catholic University of Korea. This platform is dedicated to sharing and archiving lecture materials such as practices, assignments, and sample codes for the class.

DAOR Parameter-free Embedding Framework for Large Graphs (Networks)

Network representation learning technique using structure and attributes of information networks.

Implementation and visualization of the TransE algorithm

📊 Explore diverse graph datasets for machine learning and network science, focused on enhancing Graph Neural Network applications.