GitHub

Graph Positional Autoencoders as Self-supervised Learners (GraphPAE)

accelerate==0.33.0 numpy==1.24.4 ogb==1.3.6 pandas==2.2.3 PyYAML==6.0.2 rdkit_pypi==2022.9.5 scikit_learn==1.3.2 scipy==1.8.1 torch==2.1.2+cu121 torch_geometric==2.6.1 torch_scatter==2.1.2+pt21cu121 ...
IEEE

HeMDAP: Heterogeneous Graph Self-Supervised Learning for MiRNA-Disease Association Prediction

Abstract: MiRNA-disease associations (MDAs) are particularly insightful for revealing the complex pathology of human diseases. Traditional experimental methods for MDA studies are costly, ...
IEEE

SCGRL: Graph representation learning based on edge structure contrastive self-supervised framework

Abstract: In recent years, significant advancements have been made in contrastive self-supervised learning for graphs. However, most of the existing methods start from the feature level and ignore the ...