10 citations · 12 across the 13 of their papers we have counts for
13 papers
Learning Spatio-Temporal Foundation Models from Pure Synthetic Data
Yutong Feng, Shiyuan Piao, Yutong Xia +5
Spatio-Temporal Foundation Models (STFMs) aim to learn generalizable representations of complex dynamical systems across space and time. However, existing approaches suffer from di…
FlowNet: Modeling Dynamic Spatio-Temporal Systems via Flow Propagation
Yutong Feng, Xu Liu, Yutong Xia +1
Accurately modeling complex dynamic spatio-temporal systems requires capturing flow-mediated interdependencies and context-sensitive interaction dynamics. Existing methods, predomi…
Causal Time Series Generation via Diffusion Models
Yutong Xia, Chang Xu, Yuxuan Liang +4
Time series generation (TSG) synthesizes realistic sequences and has achieved remarkable success. Among TSG, conditional models generate sequences given observed covariates, howeve…
CaPulse: Detecting Anomalies by Tuning in to the Causal Rhythms of Time Series
Yutong Xia, Yingying Zhang, Yuxuan Liang +3
Time series anomaly detection has garnered considerable attention across diverse domains. While existing methods often fail to capture the underlying mechanisms behind anomaly gene…
Reimagining Urban Science: Scaling Causal Inference with Large Language Models
Yutong Xia, Ao Qu, Yunhan Zheng +8
Urban causal research is essential for understanding the complex, dynamic processes that shape cities and for informing evidence-based policies. However, current practices are ofte…
Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey
Yuxuan Liang, Haomin Wen, Yutong Xia +6
Spatio-Temporal (ST) data science, which includes sensing, managing, and mining large-scale data across space and time, is fundamental to understanding complex systems in domains s…
AirRadar: Inferring Nationwide Air Quality in China with Deep Neural Networks
Qiongyan Wang, Yutong Xia, Siru ZHong +6
Monitoring real-time air quality is essential for safeguarding public health and fostering social progress. However, the widespread deployment of air quality monitoring stations is…
Evolutionary Greedy Algorithm for Optimal Sensor Placement Problem in Urban Sewage Surveillance
Sunyu Wang, Yutong Xia, Huanfa Chen +2
Designing a cost-effective sensor placement plan for sewage surveillance is a crucial task because it allows cost-effective early pandemic outbreak detection as supplementation for…
Using Graph Neural Networks and Frequency Domain Data for Automated Operational Modal Analysis of Populations of Structures
Xudong Jian, Yutong Xia, Gregory Duthé +3
The Population-Based Structural Health Monitoring (PBSHM) paradigm has recently emerged as a promising approach to enhance data-driven assessment of engineering structures by facil…
Predicting Parking Availability in Singapore with Cross-Domain Data: A New Dataset and A Data-Driven Approach
Huaiwu Zhang, Yutong Xia, Siru Zhong +5
The increasing number of vehicles highlights the need for efficient parking space management. Predicting real-time Parking Availability (PA) can help mitigate traffic congestion an…
DynST: Dynamic Sparse Training for Resource-Constrained Spatio-Temporal Forecasting
Hao Wu, Haomin Wen, Guibin Zhang +5
The ever-increasing sensor service, though opening a precious path and providing a deluge of earth system data for deep-learning-oriented earth science, sadly introduce a daunting…
Spatio-Temporal Field Neural Networks for Air Quality Inference
Yutong Feng, Qiongyan Wang, Yutong Xia +3
The air quality inference problem aims to utilize historical data from a limited number of observation sites to infer the air quality index at an unknown location. Considering the…
Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classification
Yutong Xia, Runpeng Yu, Yuxuan Liang +3
Graph Neural Networks have become the preferred tool to process graph data, with their efficacy being boosted through graph data augmentation techniques. Despite the evolution of a…