I find that when computing feature smoothness, the code uses the function feature_broadcast (I find it's to merge feature of a node with its neighbors).
for i in range(times):
feats = feature_broadcast(feats, G_org)
I find the formula in paper just used original feats with normalization. So I wonder why we need to calculate this feature broadcast?
The similar problem is on label_broadcast, which I think it's to remove some edges randomly. Why we need to do that?
You can find a parameter "time=0". This parameter is for us to research how fast smoothness decreases with broadcast time. Normally you can ignore that since the defualt value is 0.
I find that when computing feature smoothness, the code uses the function
feature_broadcast
(I find it's to merge feature of a node with its neighbors).I find the formula in paper just used original feats with normalization. So I wonder why we need to calculate this feature broadcast?
The similar problem is on
label_broadcast
, which I think it's to remove some edges randomly. Why we need to do that?