Graph Machine Learning
Showing 7 of 7 projects
A distributed system for learning graph embeddings from large-scale graphs with billions of entities and trillions of edges.
A Python library for machine learning on graphs and networks, offering state-of-the-art algorithms for tasks like node classification and link prediction.
An API-oriented Python framework for unsupervised learning on graphs, featuring node/graph embeddings and community detection.
A curated collection of research papers and software for explainable graph machine learning and reasoning.
An autoML framework and toolkit for automating machine learning tasks on graph-structured data.
A biomedical knowledge graph integrating 20 resources to describe 17,080 diseases with over 4 million relationships across ten biological scales.
A resource and evaluation framework for benchmarking link prediction models on large-scale, heterogeneous biomedical knowledge graphs.
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