6 citations · 12 across the 14 of their papers we have counts for
13 papers · 1 filter
Flash-OPD: Fast On-Policy Distillation
Wei Chen, Junle Chen, Yitong Yang +6
On-policy distillation (OPD) provides dense teacher supervision on student-generated trajectories, but generating and evaluating long rollouts incurs substantial training cost. Exi…
UrbanFM: Scaling Urban Spatio-Temporal Foundation Models
Wei Chen, Yuqian Wu, Junle Chen +2
Urban systems, as dynamic complex systems, continuously generate spatio-temporal data streams that encode the fundamental laws of human mobility and city evolution. While AI for Sc…
Learning from Complexity: Exploring Dynamic Sample Pruning of Spatio-Temporal Training
Wei Chen, Junle Chen, Yuqian Wu +2
Spatio-temporal forecasting is fundamental to intelligent systems in transportation, climate science, and urban planning. However, training deep learning models on the massive, oft…
Test-Time Learning of Causal Structure from Interventional Data
Wei Chen, Rui Ding, Bojun Huang +5
Supervised causal learning has shown promise in causal discovery, yet it often struggles with generalization across diverse interventional settings, particularly when intervention…
Select, then Balance: Exploring Exogenous Variable Modeling of Spatio-Temporal Forecasting
Wei Chen, Yuqian Wu, Yuanshao Zhu +4
Spatio-temporal (ST) forecasting is critical for dynamic systems, yet existing methods predominantly rely on modeling a limited set of observed target variables. In this paper, we…
Learning with Calibration: Exploring Test-Time Computing of Spatio-Temporal Forecasting
Wei Chen, Yuxuan Liang
Spatio-temporal forecasting is crucial in many domains, such as transportation, meteorology, and energy. However, real-world scenarios frequently present challenges such as signal…
Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting
Wei Chen, Yuxuan Liang
The widespread deployment of sensing devices leads to a surge in data for spatio-temporal forecasting applications such as traffic flow, air quality, and wind energy. Although spat…
Navigating Spatio-Temporal Heterogeneity: A Graph Transformer Approach for Traffic Forecasting
Jianxiang Zhou, Erdong Liu, Wei Chen +2
Traffic forecasting has emerged as a crucial research area in the development of smart cities. Although various neural networks with intricate architectures have been developed to…
ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model
Yuanshao Zhu, James Jianqiao Yu, Xiangyu Zhao +6
Generating trajectory data is among promising solutions to addressing privacy concerns, collection costs, and proprietary restrictions usually associated with human mobility analys…
Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning
Kang Luo, Yuanshao Zhu, Wei Chen +4
Trajectory modeling refers to characterizing human movement behavior, serving as a pivotal step in understanding mobility patterns. Nevertheless, existing studies typically ignore…
ST-LoRA: Low-rank Adaptation for Spatio-Temporal Forecasting
Weilin Ruan, Wei Chen, Xilin Dang +4
Spatio-temporal forecasting is essential for understanding future dynamics within real-world systems by leveraging historical data from multiple locations. Existing methods often p…
Trajectory Data Management and Mining: A Survey from Deep Learning to the LLM Era
Wei Chen, Yuanshao Zhu, Yanchuan Chang +11
Trajectory computing is a pivotal domain encompassing trajectory data management and mining, garnering widespread attention due to its crucial role in various practical application…
Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective
Jiaxi Hu, Yuehong Hu, Wei Chen +4
In long-term time series forecasting (LTSF) tasks, an increasing number of models have acknowledged that discrete time series originate from continuous dynamic systems and have att…