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torch-geometric-graph-neural-networks

PyTorch Geometric (PyG) for graph neural networks. Node classification, graph classification, link prediction with GCN, GAT, GraphSAGE, GIN layers. Message passing framework, mini-batch processing, heterogeneous graphs, neighbor sampling for large-scale learning, model explainability. Supports molecular property prediction (QM9, MoleculeNet), social networks, knowledge graphs, 3D point clouds. For non-graph deep learning use PyTorch directly; for traditional graph algorithms use NetworkX.

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์—…๋ฐ์ดํŠธ๋จ 2026. 2. 18.
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quick start

Installation and usage

PyTorch Geometric (PyG) for graph neural networks. Node classification, graph classification, link prediction with GCN, GAT, GraphSAGE, GIN layers. Message passing framework, mini-batch processing, heterogeneous graphs, neighbor sampling for large-scale learning, model explainability. Supports molecular property prediction (QM9, MoleculeNet), social networks, knowledge graphs, 3D point clouds. For non-graph deep learning use PyTorch directly; for traditional graph algorithms use NetworkX.

์„ค์น˜
$ install --globalskills.sh
์‚ฌ์šฉ๋ฒ•

์„ค์น˜ ํ›„ ํ„ฐ๋ฏธ๋„์—์„œ ๋‹ค์Œ ๋ช…๋ น์„ ์‹คํ–‰ํ•˜์—ฌ ์ด ์Šคํ‚ฌ์„ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค:

skills use torch-geometric-graph-neural-networks