Search Results for author: Yutong Xia

Found 8 papers, 3 papers with code

DynST: Dynamic Sparse Training for Resource-Constrained Spatio-Temporal Forecasting

no code implementations5 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.

Spatio-Temporal Forecasting

Spatio-Temporal Field Neural Networks for Air Quality Inference

no code implementations2 Mar 2024 Yutong Feng, Qiongyan Wang, Yutong Xia, Junlin Huang, Siru Zhong, 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.

Air Quality Inference

Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classification

no code implementations18 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.

Data Augmentation Graph Classification

LaDe: The First Comprehensive Last-mile Delivery Dataset from Industry

no code implementations19 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.

Management

DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models

1 code implementation31 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.

Decision Making Denoising

AirFormer: Predicting Nationwide Air Quality in China with Transformers

1 code implementation29 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.

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