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This repository has been archived by the owner on Nov 12, 2021. It is now read-only.
In original paper the last rule of update node vector is: $v_i^t = (1 - z_{s, i}^t) \odot v_i^{t-1} + z_{s, I}^t \odot v_i^t$. But following the code, the rules is not the same:
As I understand, there is not mistake conceptually. In paper $z$ learns how much information save, but in code it is responsible how much information forget. Am I right?
As I understand, there is not mistake conceptually. In paper $z$ learns how much information save, but in code it is responsible how much information forget. Am I right?
the readability of the code in this repository is too bad.
In original paper the last rule of update node vector is:$v_i^t = (1 - z_{s, i}^t) \odot v_i^{t-1} + z_{s, I}^t \odot v_i^t$ . But following the code, the rules is not the same:
SR-GNN/pytorch_code/model.py
Lines 45 to 47 in 90123c8
Code's rule is:
Is it mistake in paper or in code?
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