activity
20192021
most citedA Review of Location Encoding for GeoAI: Methods and Applications

170 citations · 374 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2021★ 13 cited

Time in a Box: Advancing Knowledge Graph Completion with Temporal Scopes

Ling Cai, Krzysztof Janowic, Bo Yan +2

Almost all statements in knowledge bases have a temporal scope during which they are valid. Hence, knowledge base completion (KBC) on temporal knowledge bases (TKB), where each sta…

cs.LG2021★ 170 cited

A Review of Location Encoding for GeoAI: Methods and Applications

Gengchen Mai, Krzysztof Janowicz, Yingjie Hu +5

A common need for artificial intelligence models in the broader geoscience is to represent and encode various types of spatial data, such as points (e.g., points of interest), poly…

cs.LG2020

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…

cs.DB2020★ 87 cited

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…

cs.CV2020★ 15 cited

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…

cs.LG2019★ 79 cited

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…