Papers with residual learning method

1 papers
Knowledge Graph Embedding with Atrous Convolution and Residual Learning (2020.coling-main)

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Challenge: Existing knowledge graph embedding methods are complex and require time for training and inference.
Approach: They propose an atrous convolution based knowledge graph embedding method that increases feature interactions by using atrous . they evaluate method on six benchmark datasets with different evaluation metrics .
Outcome: The proposed method achieves better results on six benchmark datasets than state-of-the-art methods on most evaluation metrics.

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