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20232026
most citedImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation

94 citations · 177 across the 16 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

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.AI2024★ 3 cited

Geolocation Representation from Large Language Models are Generic Enhancers for Spatio-Temporal Learning

Junlin He, Tong Nie, Wei Ma

In the geospatial domain, universal representation models are significantly less prevalent than their extensive use in natural language processing and computer vision. This discrep…

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…