Heterogeneous Graphs
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A PyTorch library for building and training Graph Neural Networks (GNNs) on structured and irregular data.
A comprehensive library for building and training Graph Neural Networks (GNNs) with PyTorch.
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 TensorFlow library for building Graph Neural Networks with support for heterogeneous graphs and scalable data processing.
Cleora is a fast, deterministic graph embedding engine that computes all random walks in a single matrix multiplication, requiring no GPUs or negative sampling.
A resource and evaluation framework for benchmarking link prediction models on large-scale, heterogeneous biomedical knowledge graphs.
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