TraverseNet: Unifying Space and Time in Message Passing for Traffic
Forecasting

TraverseNet: Unifying Space and Time in Message Passing for Traffic Forecasting

25 August 2021

George Karypis

Papers citing "TraverseNet: Unifying Space and Time in Message Passing for Traffic Forecasting"

5 / 5 papers shown

Title
SAMSGL: Series-Aligned Multi-Scale Graph Learning for Spatio-Temporal Forecasting Xiaobei Zou Luolin Xiong Yang Tang Jürgen Kurths AI4TS 24 1 0 05 Dec 2023
DSTCGCN: Learning Dynamic Spatial-Temporal Cross Dependencies for Traffic Forecasting Binqing Wu Ling-Hao Chen GNN AI4TS 13 3 0 02 Jul 2023
Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatio-temporal Forecasting G. Liang Prayag Tiwari Sławomir Nowaczyk Stefan Byttner F. Alonso-Fernandez DiffM 12 11 0 16 May 2023
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 41 98 0 16 May 2022
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 234 1,801 0 25 Nov 2016