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请问NN类归纳学习,拼接id的emb的物理意义是啥?
直接学习feature的归纳表达 作为节点的emb 和 学习feature + emb(id) 的归纳表达,作为节点的emb .
区别是啥,后者会效果好些吗?
另外对于后者这种,破坏了归纳学习的特点,变成了直推学习
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请问 而且为啥sage上提供 unsupervised , 而 xxgcn 不再提供了unsupervised。 原因是原理上 纯归纳学习不混合emb在非监督学习上效果烂?
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比较困惑作者 提供算法的时候是咋考虑的,肯定有自己的考量
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请问NN类归纳学习,拼接id的emb的物理意义是啥?
直接学习feature的归纳表达 作为节点的emb 和 学习feature + emb(id) 的归纳表达,作为节点的emb .
区别是啥,后者会效果好些吗?
另外对于后者这种,破坏了归纳学习的特点,变成了直推学习
The text was updated successfully, but these errors were encountered: