FighterLYL/GraphNeuralNetwork resource

Health v2 · maintenance only

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1928 stars · 472 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Companion code repository for the Chinese book '深入浅出图神经网络：GNN原理解析' (Graph Neural Networks: Principles Explained). It contains Jupyter Notebook examples covering GCN node classification, GraphSAGE, graph classification, and graph autoencoders using PyTorch.

Use cases

• learn graph neural networks from worked examples
• implement GCN node classification on the Cora dataset
• understand GraphSAGE with code
• study graph classification and graph autoencoders
• find companion code for the GNN book

When to choose

• you are reading the book and want runnable code for each chapter
• you want simple PyTorch-based GNN examples to learn from

When to avoid

• you need a production GNN framework - use PyTorch Geometric or DGL instead
• you need actively maintained code or official support

Facets

learning-resource · maturity maintenance

machine-learning deep-learning deep-learning machine-learning tutorials python graph-neural-networks gnn gcn graphsage pytorch jupyter-notebook book-companion-code chinese

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