Showing 7 of 7 projects
A Python library for machine learning on graphs and networks, offering state-of-the-art algorithms for tasks like node classification and link prediction.
A curated collection of must-read academic papers on knowledge representation learning and knowledge embedding, with an associated open-source toolkit.
An autoML framework and toolkit for automating machine learning tasks on graph-structured data.
A machine learning integrations library for TypeDB, enabling graph algorithms and Graph Neural Networks on strongly-typed graph data.
An AI system that incrementally generates scientific paper drafts by predicting links between concepts and generating text sections.
A resource and evaluation framework for benchmarking link prediction models on large-scale, heterogeneous biomedical knowledge graphs.
A PyTorch Geometric extension library for signed and directed graph neural networks, embedding, and clustering methods.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.