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

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

Zonghan Wu
Da Zheng
Shirui Pan
Quan Gan
Guodong Long
George Karypis
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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
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
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
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
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
He Zhang
Bang Wu
Xingliang Yuan
Shirui Pan
Hanghang Tong
Jian Pei
38
98
0
16 May 2022
Geometric deep learning on graphs and manifolds using mixture model CNNs
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