High sparse Knowledge Graph is a key challenge to solve the Knowledge Graph Completion task. Due to the sparsity of the KGs, there are not enough first-order neighbors to learn the features of ...
Abstract: Structured proximity matrix learning, one of the mainstream directions in clustering research, refers to learning a proximity matrix with an explicit clustering structure from the original ...
CERDA-HOSR is a novel computational method that leverages higher-order graph attention networks and graph convolutional networks to predict ceRNA-disease associations. data.xlsx: Dataset1 comprises ...
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