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"

7 / 7 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
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 34 3 0 30 Aug 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 29 7 0 05 Nov 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
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