no code implementations • 5 Mar 2024 • Hao Wu, Haomin Wen, Guibin Zhang, Yutong Xia, Kai Wang, Yuxuan Liang, Yu Zheng, Kun Wang
In this paper, we introduce for the first time the concept of spatio-temporal data dynamic sparse training and are committed to adaptively, dynamically filtering important sensor distributions.
no code implementations • 2 Mar 2024 • Yutong Feng, Qiongyan Wang, Yutong Xia, Junlin Huang, Siru Zhong, Kun Wang, Shifen Cheng, Yuxuan Liang
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.
no code implementations • 18 Jan 2024 • Yutong Xia, Runpeng Yu, Yuxuan Liang, Xavier Bresson, Xinchao Wang, Roger Zimmermann
Graph Neural Networks (GNNs) have become the preferred tool to process graph data, with their efficacy being boosted through graph data augmentation techniques.
no code implementations • 19 Jun 2023 • Lixia Wu, Haomin Wen, Haoyuan Hu, Xiaowei Mao, Yutong Xia, Ergang Shan, Jianbin Zhen, Junhong Lou, Yuxuan Liang, Liuqing Yang, Roger Zimmermann, Youfang Lin, Huaiyu Wan
In this paper, we introduce \texttt{LaDe}, the first publicly available last-mile delivery dataset with millions of packages from the industry.
1 code implementation • NeurIPS 2023 • Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, Roger Zimmermann
To mitigate these limitations, we introduce the LargeST benchmark dataset.
Ranked #1 on Traffic Prediction on LargeST
1 code implementation • 31 Jan 2023 • Haomin Wen, Youfang Lin, Yutong Xia, Huaiyu Wan, Qingsong Wen, Roger Zimmermann, Yuxuan Liang
Spatio-temporal graph neural networks (STGNN) have emerged as the dominant model for spatio-temporal graph (STG) forecasting.
1 code implementation • 29 Nov 2022 • Yuxuan Liang, Yutong Xia, Songyu Ke, Yiwei Wang, Qingsong Wen, Junbo Zhang, Yu Zheng, Roger Zimmermann
Air pollution is a crucial issue affecting human health and livelihoods, as well as one of the barriers to economic and social growth.