Samuel Leventhal

Hi @HiLiHeYi , I can only speak from personal experience but this has been a large obstical for me. What I have done to summarize depends on whether or not...

Hi Heyi, Before I explain approaching the problem with a union I wanted to mention a couple of things that might save you time in the event you can avoid...

Graphsage will either be given as a parameter a max node degree to adhere to or observe the node with the highest degree and when building the adjacency matrix will...

The negative sampling is not used in the supervised case. @ninesky110 will you elaborate on how it did not work? The embeddings learned during unsupervised should be different as things...

right, I agree, so maybe I'm not understanding the question. My point was that if sampling is what you would like to know more about (e.g. the difference in embedding)...

I believe this behavior might be a result of the custom loss function used by graphsage to promote learning graph embeddings where similar nodes are nearer and disparate nodes are...