pytorch_geometric and stellargraph
PyTorch Geometric and StellarGraph are competitors offering overlapping GNN implementations, though PyTorch Geometric is more mature and widely adopted (23.5K vs 3K stars, 1000x higher downloads) with tighter PyTorch integration, while StellarGraph provides a higher-level API built on TensorFlow/Keras that may appeal to users preferring that ecosystem.
About pytorch_geometric
pyg-team/pytorch_geometric
Graph Neural Network Library for PyTorch
Provides a message-passing API for implementing custom GNN layers and pre-built convolution operators (GCNConv, EdgeConv, etc.) that handle node aggregation and feature propagation. Supports heterogeneous graphs, dynamic temporal graphs, and large-scale models with millions of nodes, alongside specialized data loaders for mini-batch training on both small and giant graphs. Includes built-in benchmark datasets and graph transforms for point clouds and 3D meshes, with `torch.compile` and multi-GPU support for production deployments.
About stellargraph
stellargraph/stellargraph
StellarGraph - Machine Learning on Graphs
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