GNN初學筆記（一）—— Relational inductive biases, deep learning, and graph networks簡要解析
GNN初學筆記（一）—— Relational inductive biases, deep learning, and graph networks文獻學習 （我會在每個術語解釋後面加入自己的理解，若有錯誤懇請指正） 這篇文獻首先闡釋AI如何模擬人類的學習能力，即組合泛化能力（combinatorial generalization），總結了目前深度學習「端到端」（end to end）的模型，
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相關文章
- 1. GNN新作《Relational inductive biases，deep learning，and graph networks》讀書筆記
- 2. Relational inductive biases, deep learning, and graph networks
- 3. 讀書筆記7：Relational inductive biases, deep learning, and graph networks
- 4. Relational inductive biases, deep learning, and graph networks 論文導讀，DeepMind圖網絡
- 5. 《Relational inductive biases, deep learning, and graph networks》論文解讀（轉載）
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- 8. Neural Networks and Deep Learning 學習筆記（一）
- 9. neural networks and deep learning 筆記（一）
- 10. GraphSAINT: Graph Sampling Based Inductive Learning Method