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图深度学习(葡萄书),在线阅读地址: https://datawhalechina.github.io/grape-book

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deep-learning gnn graph graph-neural-networks machine-learning tutorial

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grape-book's Issues

关于差集的 notaion 问题

image

在线教程的2.3.5节中的差集应使用反斜杠: $V \setminus V'$V \setminus V')或减号: $V - V'$V - V'),而不是斜杠/
斜杠/在数学中常用来表示商集,如集合 $A$ 在等价关系 $\sim$ 下的商集 $V/_{\sim}$ .

some mistakes

  1. 第四章图表示学习 4.1.2 一般的随机游走: 深度游走 部分,公式:
    image
    应该更正为:
    image
    fou'ze
    最后一项不对内积进行非线性变换无法保证结果为正,进而无法进行对数操作
  2. 第四章图表示学习 4.1.3 有偏的随机游走:Node2Vec 部分,对图4.4的描述应该将访问概率更改为访问权重, 对权重进行归一化得到的才是概率
  3. 第五章图卷积神经网络 5.1.3 图卷积神经网络 部分,公式
    image
    多写了一个"="

PS:(夹带私货): 学习笔记(部分), 里面是对部分章节的整理,也掺杂了一些自己的理解

2.3.2 建议修正

度分布 P(d):表示随机选择到节点度为d的概率
建议改为
度分布 P(d):表示随机选择的节点的度为d的概率

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