Feb 8, 2022 · Title:Rethinking Graph Convolutional Networks in Knowledge Graph Completion. Authors:Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu. View a PDF ...
Graph convolutional networks (GCNs)—which are effective in modeling graph structures—have been increasingly popular in knowledge graph completion (KGC).
Rethinking Graph Convolutional Networks in Knowledge Graph Completion. This is the code of paper Rethinking Graph Convolutional Networks in Knowledge Graph ...
Duration: 15:00
Posted: Sep 12, 2022
Posted: Sep 12, 2022
Rethinking Graph Convolutional Networks in Knowledge Graph Completion. February 2022. Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu.
People also ask
Why do convolutional neural networks CNNs fail on graphs?
What is the difference between GNN and knowledge graph?
What is the difference between graph convolutional networks and GNN?
What is the difference between a graph and a knowledge graph?
Jul 4, 2023 · Knowledge embedding based graph convolutional network. In ... Rethinking graph convolutional networks in knowledge graph completion.
Graph convolutional networks (GCNs) -- which are effective in modeling graph structures -- have been increasingly popular in knowledge graph completion ...
Temporal knowledge graph completion (TKGC) has become a popular approach for reasoning over the event and temporal knowledge graphs, targeting the completion of ...
[PDF] Rethinking Knowledge Graph Propagation for Zero-Shot Learning
www.cs.cmu.edu › ~epxing › papers
Graph convolutional neural networks have recently shown great potential for the task of zero-shot learning. These models are highly sample efficient as ...