Multi-Graph Inductive Representation Learning for Large-Scale Urban Rail Demand Prediction under Disruptions

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Multi-Graph Inductive Representation Learning for Large-Scale Urban Rail Demand Prediction under Disruptions

28 August 2024

Dang Viet Anh Nguyen

J. Victor Flensburg

Fabrizio Cerreto

Bianca Pascariu

Paola Pellegrini

Carlos Lima Azevedo

Filipe Rodrigues

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Papers citing "Multi-Graph Inductive Representation Learning for Large-Scale Urban Rail Demand Prediction under Disruptions"

9 / 9 papers shown

Title
On the importance of stationarity, strong baselines and benchmarks in transport prediction problems Filipe Rodrigues AI4TS 64 2 0 06 Mar 2022
Identifying the Factors that Influence Urban Public Transit Demand Armstrong Aboah L. Johnson Setul M. Shah AI4TS 25 3 0 16 Nov 2021
Online Metro Origin-Destination Prediction via Heterogeneous Information Aggregation Lingbo Liu Yuying Zhu Guanbin Li Ziyi Wu Lei Bai Liang Lin AI4TS 75 33 0 02 Jul 2021
Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network Jintao Ke Xiaoran Qin Hai Yang Zhengfei Zheng Zheng Zhu Jieping Ye AI4TS 58 155 0 17 Oct 2019
T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction Ling Zhao Yujiao Song Chao Zhang Yu Liu Pu Wang Tao Lin Min Deng Haifeng Li AI4TS 86 2,030 0 12 Nov 2018
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting Ting Yu Haoteng Yin Zhanxing Zhu GNN AI4TS 130 3,728 0 14 Sep 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 514 15,319 0 07 Jun 2017
Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction Junbo Zhang Yu Zheng Dekang Qi 3DPC AI4TS 104 2,059 0 01 Oct 2016
XGBoost: A Scalable Tree Boosting System Tianqi Chen Carlos Guestrin 812 39,062 0 09 Mar 2016