Comments (4)
it seems the attention matrix A is kept same in all propagation layers (within each epoch), I am wondering shouldn't we calculate attention matrix for each layer separately based on node embeddings in that layer according to equation 4 and 5? @xiangwang1223
from knowledge_graph_attention_network.
Only consider the cf part, is the code you released equal to NGCF model. Neural Graph Collaborative Filtering ?
from knowledge_graph_attention_network.
it seems the attention matrix A is kept same in all propagation layers (within each epoch), I am wondering shouldn't we calculate attention matrix for each layer separately based on node embeddings in that layer according to equation 4 and 5? @xiangwang1223
I also have the same question. Moreover, the attention scores on the knowledge graph are very hard to compute, because this process costs too many memories.Can the process be optimised by multiprocessing?
from knowledge_graph_attention_network.
The attention score is actually fixed during one epoch training.But attention score in next epoch(also fixed) is different from attention score in this epoch. Maybe, Updating attention score in different layers of one epoch can achieve a little better performence .However, In my opinion, attention score is updated this way can try to avoid memory-out error.
from knowledge_graph_attention_network.
Related Issues (20)
- I have a question about kg_final.txt HOT 1
- I have a question about memory growth HOT 1
- ERROR: loss@phase2 is nan HOT 1
- Yelp dataset is missing HOT 2
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- Question about data partition: did you use validation data for selecting best models?
- 卡在epoch0
- 采用TransR方法训练实体表示的作用? HOT 1
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- IndexError: too many indices for array
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- UnicodeDecodeError HOT 1
- how to print the attention score with tensorflow?
- how to calculate the %improv?
- Item_list.txt is missing spaces in the yelp2018
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