3 citations · 5 across the 5 of their papers we have counts for
5 papers
Spatial-Temporal Cross-View Contrastive Pre-training for Check-in Sequence Representation Learning
Letian Gong, Huaiyu Wan, Shengnan Guo +6
The rapid growth of location-based services (LBS) has yielded massive amounts of data on human mobility. Effectively extracting meaningful representations for user-generated check-…
UrbanLLM: Autonomous Urban Activity Planning and Management with Large Language Models
Yue Jiang, Qin Chao, Yile Chen +3
Location-based services play an critical role in improving the quality of our daily lives. Despite the proliferation of numerous specialized AI models within spatio-temporal contex…
SAGDFN: A Scalable Adaptive Graph Diffusion Forecasting Network for Multivariate Time Series Forecasting
Yue Jiang, Xiucheng Li, Yile Chen +4
Time series forecasting is essential for our daily activities and precise modeling of the complex correlations and shared patterns among multiple time series is essential for impro…
Semantic-Enhanced Representation Learning for Road Networks with Temporal Dynamics
Yile Chen, Xiucheng Li, Gao Cong +2
In this study, we introduce a novel framework called Toast for learning general-purpose representations of road networks, along with its advanced counterpart DyToast, designed to e…
Points-of-Interest Relationship Inference with Spatial-enriched Graph Neural Networks
Yile Chen, Xiucheng Li, Gao Cong +5
As a fundamental component in location-based services, inferring the relationship between points-of-interests (POIs) is very critical for service providers to offer good user exper…