4 citations · 6 across the 7 of their papers we have counts for
7 papers
T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation
Cuiying Huo, Di Jin, Yawen Li +3
Graph Neural Networks (GNNs) have been a prevailing technique for tackling various analysis tasks on graph data. A key premise for the remarkable performance of GNNs relies on comp…
Distributed Graph Neural Network Training: A Survey
Yingxia Shao, Hongzheng Li, Xizhi Gu +6
Graph neural networks (GNNs) are a type of deep learning models that are trained on graphs and have been successfully applied in various domains. Despite the effectiveness of GNNs,…
Adaptive Dual Channel Convolution Hypergraph Representation Learning for Technological Intellectual Property
Yuxin Liu, Yawen Li, Yingxia Shao +1
In the age of big data, the demand for hidden information mining in technological intellectual property is increasing in discrete countries. Definitely, a considerable number of gr…
Embedding Representation of Academic Heterogeneous Information Networks Based on Federated Learning
Junfu Wang, Yawen Li, Meiyu Liang +1
Academic networks in the real world can usually be portrayed as heterogeneous information networks (HINs) with multi-type, universally connected nodes and multi-relationships. Some…
Unsupervised Semantic Representation Learning of Scientific Literature Based on Graph Attention Mechanism and Maximum Mutual Information
Hongrui Gao, Yawen Li, Meiyu Liang +1
Since most scientific literature data are unlabeled, this makes unsupervised graph-based semantic representation learning crucial. Therefore, an unsupervised semantic representatio…
A sentiment analysis model for car review texts based on adversarial training and whole word mask BERT
Xingchen Liu, Yawen Li, Yingxia Shao +2
In the field of car evaluation, more and more netizens choose to express their opinions on the Internet platform, and these comments will affect the decision-making of buyers and t…
Semantic Similarity Computing for Scientific Academic Conferences fused with domain features
Runyu Yu, Yawen Li, Ang Li
Aiming at the problem that the current general-purpose semantic text similarity calculation methods are difficult to use the semantic information of scientific academic conference…