87 citations · 191 across the 5 of their papers we have counts for
5 papers
Isometric Graph Neural Networks
Matthew Walker, Bo Yan, Yiou Xiao +2
Many tasks that rely on representations of nodes in graphs would benefit if those representations were faithful to distances between nodes in the graph. Geometric techniques to ext…
SE-KGE: A Location-Aware Knowledge Graph Embedding Model for Geographic Question Answering and Spatial Semantic Lifting
Gengchen Mai, Krzysztof Janowicz, Ling Cai +5
Learning knowledge graph (KG) embeddings is an emerging technique for a variety of downstream tasks such as summarization, link prediction, information retrieval, and question answ…
Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells
Gengchen Mai, Krzysztof Janowicz, Bo Yan +3
Unsupervised text encoding models have recently fueled substantial progress in NLP. The key idea is to use neural networks to convert words in texts to vector space representations…
TransGCN:Coupling Transformation Assumptions with Graph Convolutional Networks for Link Prediction
Ling Cai, Bo Yan, Gengchen Mai +2
Link prediction is an important and frequently studied task that contributes to an understanding of the structure of knowledge graphs (KGs) in statistical relational learning. Insp…
Contextual Graph Attention for Answering Logical Queries over Incomplete Knowledge Graphs
Gengchen Mai, Krzysztof Janowicz, Bo Yan +3
Recently, several studies have explored methods for using KG embedding to answer logical queries. These approaches either treat embedding learning and query answering as two separa…