Data-Driven Traffic Assignment: A Novel Approach for Learning Traffic Flow Patterns Using a Graph Convolutional Neural Network

21 February 2022

Papers citing "Data-Driven Traffic Assignment: A Novel Approach for Learning Traffic Flow Patterns Using a Graph Convolutional Neural Network"

7 / 7 papers shown

Title
Learning to Simulate Complex Physics with Graph Networks Alvaro Sanchez-Gonzalez Jonathan Godwin Tobias Pfaff Rex Ying J. Leskovec Peter W. Battaglia PINN AI4CE 148 1,104 0 21 Feb 2020
Graph Markov Network for Traffic Forecasting with Missing Data Zhiyong Cui Longfei Lin Ziyuan Pu Yinhai Wang AI4TS 52 97 0 10 Dec 2019
Graph Neural Networks: A Review of Methods and Applications Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun AI4CE GNN 1.1K 5,551 0 20 Dec 2018
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 100 2,033 0 12 Nov 2018
Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting Zhiyong Cui Kristian C. Henrickson Ruimin Ke Ziyuan Pu Yinhai Wang GNN AI4TS 140 751 0 20 Feb 2018
Predicting Station-level Hourly Demands in a Large-scale Bike-sharing Network: A Graph Convolutional Neural Network Approach Lei Lin Zhengbing He S. Peeta GNN 45 375 0 13 Dec 2017
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering M. Defferrard Xavier Bresson P. Vandergheynst GNN 371 7,680 0 30 Jun 2016