Showing 9 of 9 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.
Easy link prediction tool
Graph embedding framework implementing TransE, TransH, TransR, TransD, and TransSparse models for knowledge graph representation learning.
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