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Thanks for your interest.
If you indicate the adjacency matrix A in Eq(3), then it is yes. The graph is the same for all input data. But when it comes to the attention part in Eq(6)-(8), each sample can get different attention weights as the attentions are computed based on the each sample and the global sensor embeddings.
Potentially yes. I think it depends on your task. You could use the embedding before the outlayer potentially for any downstream task when the learned representations have some good properties, such as clustering.
Thanks for your excellent work,
According to your code , I want to know if the X_data in the same batch share the same learned graph ?
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