activity
20222024
most citedImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation

94 citations · 175 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2024★ 18 cited

Joint Estimation and Prediction of City-wide Delivery Demand: A Large Language Model Empowered Graph-based Learning Approach

Tong Nie, Junlin He, Yuewen Mei +4

The proliferation of e-commerce and urbanization has significantly intensified delivery operations in urban areas, boosting the volume and complexity of delivery demand. Data-drive…

cs.LG2024★ 8 cited

Channel-Aware Low-Rank Adaptation in Time Series Forecasting

Tong Nie, Yuewen Mei, Guoyang Qin +2

The balance between model capacity and generalization has been a key focus of recent discussions in long-term time series forecasting. Two representative channel strategies are clo…

cs.LG2024

Generalizable Implicit Neural Representation As a Universal Spatiotemporal Traffic Data Learner

Tong Nie, Guoyang Qin, Wei Ma +1

. Spatiotemporal Traffic Data (STTD) meas…

cs.LG2024★ 9 cited

Spatiotemporal Implicit Neural Representation as a Generalized Traffic Data Learner

Tong Nie, Guoyang Qin, Wei Ma +1

Spatiotemporal Traffic Data (STTD) measures the complex dynamical behaviors of the multiscale transportation system. Existing methods aim to reconstruct STTD using low-dimensional…

cs.LG2023★ 94 cited

ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation

Tong Nie, Guoyang Qin, Wei Ma +2

Missing data is a pervasive issue in both scientific and engineering tasks, especially for the modeling of spatiotemporal data. This problem attracts many studies to contribute to…

cs.LG2023★ 1 cited

Contextualizing MLP-Mixers Spatiotemporally for Urban Data Forecast at Scale

Tong Nie, Guoyang Qin, Lijun Sun +3

Spatiotemporal traffic data (STTD) displays complex correlational structures. Extensive advanced techniques have been designed to capture these structures for effective forecasting…

math.OC2023

A Macro-Micro Approach to Reconstructing Vehicle Trajectories on Multi-Lane Freeways with Lane Changing

Xuejian Chen, Guoyang Qin, Toru Seo +2

Vehicle trajectories can offer the most precise and detailed depiction of traffic flow and serve as a critical component in traffic management and control applications. Various tec…

stat.ML2023★ 3 cited

Towards better traffic volume estimation: Jointly addressing the underdetermination and nonequilibrium problems with correlation-adaptive GNNs

Tong Nie, Guoyang Qin, Yunpeng Wang +1

Traffic volume is an indispensable ingredient to provide fine-grained information for traffic management and control. However, due to limited deployment of traffic sensors, obtaini…

stat.ML2022★ 42 cited

Correlating sparse sensing for large-scale traffic speed estimation: A Laplacian-enhanced low-rank tensor kriging approach

Tong Nie, Guoyang Qin, Yunpeng Wang +1

Traffic speed is central to characterizing the fluidity of the road network. Many transportation applications rely on it, such as real-time navigation, dynamic route planning, and…