Dynamic Origin-Destination Matrix Prediction with Line Graph Neural Networks and Kalman Filter

1 May 2019

Papers citing "Dynamic Origin-Destination Matrix Prediction with Line Graph Neural Networks and Kalman Filter"

8 / 8 papers shown

Title
Large-Scale OD Matrix Estimation with A Deep Learning Method Zheli Xiong Defu Lian Enhong Chen Gang Chen Xiaomin Cheng 21 0 0 09 Oct 2023
Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction Xinke Jiang Dingyi Zhuang Xianghui Zhang Hao Chen Jiayuan Luo Xiaowei Gao 26 21 0 16 Jun 2023
Traffic Prediction with Transfer Learning: A Mutual Information-based Approach Yunjie Huang Xiaozhuang Song Yuanshao Zhu Shiyao Zhang James J. Q. Yu AI4TS 38 11 0 13 Mar 2023
Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural Networks Qingyi Wang Shenhao Wang Dingyi Zhuang Haris N. Koutsopoulos Jinhua Zhao AI4TS 19 19 0 07 Mar 2023
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction Liangzhe Han Xiaojian Ma Leilei Sun Bowen Du Yanjie Fu Weifeng Lv Hui Xiong AI4TS 42 26 0 30 Jun 2022
Learning Geo-Contextual Embeddings for Commuting Flow Prediction Zhicheng Liu Fabio Miranda Weiting Xiong Junyan Yang Qiao Wang Claudio T. Silva AI4TS 36 71 0 04 May 2020
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 38 151 0 17 Oct 2019
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Xingjian Shi Zhourong Chen Hao Wang Dit-Yan Yeung W. Wong W. Woo 239 7,921 0 13 Jun 2015