arXiv綜述論文「Graph Neural Networks: A Review of Methods and Applications」
arXiv於2019年7月10日上載的GNN綜述論文「Graph Neural Networks: A Review of Methods and Applications「。 摘要：許多學習任務需要處理圖數據，該圖數據包含元素之間的豐富關係信息。建模物理系統、學習分子指紋、預測蛋白質界面以及對疾病進行分類都需要一個模型從圖輸入學習。在其他如文本和圖像之類非結構數據學習的領域中，對提取的結構推理，
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相關文章
- 1. 《圖神經網絡綜述》Graph Neural Networks: A Review of Methods and Applications
- 2. 《Graph Neural Networks: A Review of Methods and Applications》圖網絡綜述 -- 解析筆記
- 3. 【GNN綜述1-模型與應用】 Graph Neural Networks: A Review of Methods and Applications
- 4. 《Graph Neural Networks: A Review of Methods and Applications》閱讀筆記
- 5. Paper：《Graph Neural Networks: A Review of Methods and Applications》翻譯與解讀
- 6. Graph Neural Networks: A Review of Methods and Applications閱讀筆記
- 7. Graph Neural Networks: A Review of Methods and Applications學習筆記
- 8. Applications of Graph Neural Networks
- 9. Graph Neural Networks: A Review of Methods and Applications（圖神經網絡：方法與應用綜述）
- 10. 綜述論文「A Survey of Zero-Shot Learning: Settings, Methods, and Applications」