Spatial Aggregation and Temporal Convolution Networks for Real-time
Kriging

Spatial Aggregation and Temporal Convolution Networks for Real-time Kriging

24 September 2021

Papers citing "Spatial Aggregation and Temporal Convolution Networks for Real-time Kriging"

17 / 17 papers shown

Title
Spatio-Temporal Graph Neural Network for Urban Spaces: Interpolating Citywide Traffic Volume Silke K. Kaiser Filipe Rodrigues Carlos Lima Azevedo Lynn H. Kaack AI4TS GNN 19 0 0 07 May 2025
Network-wide Freeway Traffic Estimation Using Sparse Sensor Data: A Dirichlet Graph Auto-Encoder Approach Qishen Zhou Yifan Zhang Michail A. Makridis Anastasios Kouvelas Yibing Wang Simon Hu 52 0 0 20 Mar 2025
From Incomplete Coarse-Grained to Complete Fine-Grained: A Two-Stage Framework for Spatiotemporal Data Reconstruction Ziyu Sun Haoyang Su E. Wang Funing Yang Yongjian Yang Wenbin Liu AI4TS DiffM 31 0 0 05 Oct 2024
Joint Estimation and Prediction of City-wide Delivery Demand: A Large Language Model Empowered Graph-based Learning Approach Tong Nie Junlin He Yuewen Mei Guoyang Qin Guilong Li Jian Sun Wei Ma 37 3 0 30 Aug 2024
Advancing Transportation Mode Share Analysis with Built Environment: Deep Hybrid Models with Urban Road Network Dingyi Zhuang Qingyi Wang Yunhan Zheng Xiaotong Guo Shenhao Wang Haris N. Koutsopoulos Jinhua Zhao 19 0 0 23 May 2024
Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations G. Felice Andrea Cini Daniele Zambon Vladimir V. Gusev Cesare Alippi 34 6 0 19 Feb 2024
Non-Neighbors Also Matter to Kriging: A New Contrastive-Prototypical Learning Zhishuai Li Yunhao Nie Ziyue Li Lei Bai Yisheng Lv Rui Zhao 13 5 0 23 Jan 2024
KITS: Inductive Spatio-Temporal Kriging with Increment Training Strategy Qianxiong Xu Cheng Long Ziyue Li Sijie Ruan Rui Zhao Zhishuai Li 31 7 0 05 Nov 2023
Towards Unifying Diffusion Models for Probabilistic Spatio-Temporal Graph Learning Junfeng Hu Xu Liu Zhencheng Fan Yuxuan Liang Roger Zimmermann AI4CE DiffM 28 7 0 26 Oct 2023
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection Ming Jin Huan Yee Koh Qingsong Wen Daniele Zambon Cesare Alippi G. I. Webb Irwin King Shirui Pan AI4TS AI4CE 41 143 0 07 Jul 2023
ST-GIN: An Uncertainty Quantification Approach in Traffic Data Imputation with Spatio-temporal Graph Attention and Bidirectional Recurrent United Neural Networks Zepu Wang Dingyi Zhuang Yankai Li Jinhua Zhao Peng Sun Shenhao Wang Yulin Hu GNN AI4TS 27 15 0 10 May 2023
Towards better traffic volume estimation: Jointly addressing the underdetermination and nonequilibrium problems with correlation-adaptive GNNs Tong Nie Guoyang Qin Yunpeng Wang Jiangming Sun 34 14 0 10 Mar 2023
Deep hybrid model with satellite imagery: how to combine demand modeling and computer vision for behavior analysis? Qingyi Wang Shenhao Wang Yunhan Zheng Hongzhou Lin Xiaohu Zhang Jinhua Zhao Joan Walker 13 9 0 07 Mar 2023
Correlating sparse sensing for large-scale traffic speed estimation: A Laplacian-enhanced low-rank tensor kriging approach Tong Nie Guoyang Qin Yunpeng Wang Jian Sun 30 24 0 21 Oct 2022
Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks Dingyi Zhuang Shenhao Wang Haris N. Koutsopoulos Jinhua Zhao 26 33 0 11 Aug 2022
Decoupling Long- and Short-Term Patterns in Spatiotemporal Inference Junfeng Hu Yuxuan Liang Zhencheng Fan Ying Zhang Yifang Yin Roger Zimmermann AI4TS 52 11 0 16 Sep 2021
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 189 916 0 02 Mar 2020