8 citations · 16 across the 8 of their papers we have counts for
8 papers
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…
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…
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…
JAS-GAN: Generative Adversarial Network Based Joint Atrium and Scar Segmentations on Unbalanced Atrial Targets
Jun Chen, Guang Yang, Habib Khan +7
Automated and accurate segmentations of left atrium (LA) and atrial scars from late gadolinium-enhanced cardiac magnetic resonance (LGE CMR) images are in high demand for quantifyi…
A multi-label classification method using a hierarchical and transparent representation for paper-reviewer recommendation
Dong Zhang, Shu Zhao, Zhen Duan +3
Paper-reviewer recommendation task is of significant academic importance for conference chairs and journal editors. How to effectively and accurately recommend reviewers for the su…
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…
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…
Direct detection of pixel-level myocardial infarction areas via a deep-learning algorithm
Chenchu Xu, Lei Xu, Zhifan Gao +7
Accurate detection of the myocardial infarction (MI) area is crucial for early diagnosis planning and follow-up management. In this study, we propose an end-to-end deep-learning al…