14 citations · 38 across the 8 of their papers we have counts for
9 papers
Spatial-Agent: Agentic Geo-spatial Reasoning with Scientific Core Concepts
Riyang Bao, Cheng Yang, Dazhou Yu +3
Geospatial reasoning is essential for real-world applications such as urban analytics, transportation planning, and disaster response. However, existing LLM-based agents often fail…
PolyhedronNet: Representation Learning for Polyhedra with Surface-attributed Graph
Dazhou Yu, Genpei Zhang, Liang Zhao
Ubiquitous geometric objects can be precisely and efficiently represented as polyhedra. The transformation of a polyhedron into a vector, known as polyhedra representation learning…
Spatial-RAG: Spatial Retrieval Augmented Generation for Real-World Geospatial Reasoning Questions
Dazhou Yu, Riyang Bao, Ruiyu Ning +3
Answering real-world geospatial questions--such as finding restaurants along a travel route or amenities near a landmark--requires reasoning over both geographic relationships and…
Transferable Unsupervised Outlier Detection Framework for Human Semantic Trajectories
Zheng Zhang, Hossein Amiri, Dazhou Yu +3
Semantic trajectories, which enrich spatial-temporal data with textual information such as trip purposes or location activities, are key for identifying outlier behaviors critical…
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…
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning
Yuyang Gao, Siyi Gu, Junji Jiang +3
As the societal impact of Deep Neural Networks (DNNs) grows, the goals for advancing DNNs become more complex and diverse, ranging from improving a conventional model accuracy metr…
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…