activity
20192024
most citedHyperbolic Hierarchical Knowledge Graph Embeddings for Link Prediction in Low Dimensions

4 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2024★ 1 cited

Why are hyperbolic neural networks effective? A study on hierarchical representation capability

Shicheng Tan, Huanjing Zhao, Shu Zhao +1

Hyperbolic Neural Networks (HNNs), operating in hyperbolic space, have been widely applied in recent years, motivated by the existence of an optimal embedding in hyperbolic space t…

cs.LG2022★ 4 cited

Hyperbolic Hierarchical Knowledge Graph Embeddings for Link Prediction in Low Dimensions

Wenjie Zheng, Wenxue Wang, Shu Zhao +1

Knowledge graph embeddings (KGE) have been validated as powerful methods for inferring missing links in knowledge graphs (KGs) that they typically map entities into Euclidean space…

cs.CL2022★ 1 cited

Coherence-Based Distributed Document Representation Learning for Scientific Documents

Shicheng Tan, Shu Zhao, Yanping Zhang

Distributed document representation is one of the basic problems in natural language processing. Currently distributed document representation methods mainly consider the context i…

cs.LG2019★ 1 cited

Discriminative Consistent Domain Generation for Semi-supervised Learning

Jun Chen, Heye Zhang, Yanping Zhang +6

Deep learning based task systems normally rely on a large amount of manually labeled training data, which is expensive to obtain and subject to operator variations. Moreover, it do…

eess.IV2019

Direct Quantification for Coronary Artery Stenosis Using Multiview Learning

Dong Zhang, Guang Yang, Shu Zhao +3

The quantification of the coronary artery stenosis is of significant clinical importance in coronary artery disease diagnosis and intervention treatment. It aims to quantify the mo…