Decompressing Knowledge Graph Representations for Link Prediction
Table 6: The robustness comparison between DeCom and original models on FB15k-237 validation set.
['Model', '[ITALIC] de', '^ [ITALIC] de', '[ITALIC] dr', '^ [ITALIC] dr', 'MRR', 'H@10']
2) Learning more robust features. To further understand this fact, decompressing functions are designed to keep the size of input features (original embedding) and output ones the same. Specifically, we set the output feature size of F-DeCom and C-DeCom the same as the input embedding dimension, i.e., 100. Despite there is no increase in embedding size, the DeCom models still achieve the performance improvement, suggesting that they could learn more robust embeddings.