74 citations · 102 across the 5 of their papers we have counts for
5 papers
PolygonGNN: Representation Learning for Polygonal Geometries with Heterogeneous Visibility Graph
Dazhou Yu, Yuntong Hu, Yun Li +1
Polygon representation learning is essential for diverse applications, encompassing tasks such as shape coding, building pattern classification, and geographic question answering.…
Self-consistent Deep Geometric Learning for Heterogeneous Multi-source Spatial Point Data Prediction
Dazhou Yu, Xiaoyun Gong, Yun Li +2
Multi-source spatial point data prediction is crucial in fields like environmental monitoring and natural resource management, where integrating data from various sensors is the ke…
Graph Neural Network for spatiotemporal data: methods and applications
Yun Li, Dazhou Yu, Zhenke Liu +3
In the era of big data, there has been a surge in the availability of data containing rich spatial and temporal information, offering valuable insights into dynamic systems and pro…
Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey
Chen Ling, Xujiang Zhao, Jiaying Lu +21
Large language models (LLMs) have significantly advanced the field of natural language processing (NLP), providing a highly useful, task-agnostic foundation for a wide range of app…
Deep Spatial Domain Generalization
Dazhou Yu, Guangji Bai, Yun Li +1
Spatial autocorrelation and spatial heterogeneity widely exist in spatial data, which make the traditional machine learning model perform badly. Spatial domain generalization is a…