1 code implementation • 4 Dec 2023 • Tong Nie, Guoyang Qin, Wei Ma, Yuewen Mei, Jian Sun
The exploitation of the inherent structures of spatiotemporal data enables our model to learn balanced signal-noise representations, making it versatile for a variety of imputation problems.
1 code implementation • 4 Jul 2023 • Tong Nie, Guoyang Qin, Lijun Sun, Wei Ma, Yu Mei, Jian Sun
Spatiotemporal urban data (STUD) displays complex correlational patterns.
1 code implementation • 10 Mar 2023 • Tong Nie, Guoyang Qin, Yunpeng Wang, Jian Sun
Traffic volume is an indispensable ingredient to provide fine-grained information for traffic management and control.
1 code implementation • 21 Oct 2022 • Tong Nie, Guoyang Qin, Yunpeng Wang, Jian Sun
In addition, sensors are prone to error or missing data due to various kinds of reasons, speeds from these sensors can become highly noisy.
1 code implementation • 19 May 2022 • Tong Nie, Guoyang Qin, Jian Sun
Rapid advances in sensor, wireless communication, cloud computing and data science have brought unprecedented amount of data to assist transportation engineers and researchers in making better decisions.