As a specific case of graph transfer learning, unsupervised domain adapt...
The objective of topic inference in research proposals aims to obtain th...
Temporal knowledge graph (TKG) reasoning aims to predict the future miss...
Graph representation learning aims to effectively encode high-dimensiona...
Feature transformation for AI is an essential task to boost the effectiv...
Graph contrastive learning (GCL) has been an emerging solution for graph...
Funding agencies are largely relied on a topic matching between domain
e...
The peer merit review of research proposals has been the major mechanism...
With the growth of the academic engines, the mining and analysis acquisi...
To advance the development of science and technology, research proposals...
Data augmentation aims to generate new and synthetic features from the
o...
Knowledge graph embedding (KGE) models learn to project symbolic entitie...
Most researches for knowledge graph completion learn representations of
...
While Graph Neural Network (GNN) has shown superiority in learning node
...