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GREAD: Graph Neural Reaction-Diffusion Networks

GREAD: Graph Neural Reaction-Diffusion Networks

25 November 2022
Jeongwhan Choi
Seoyoung Hong
Noseong Park
Sung-Bae Cho
    DiffM
    GNN
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Papers citing "GREAD: Graph Neural Reaction-Diffusion Networks"

13 / 13 papers shown
Title
Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks
Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks
Z. Liu
Xiaoda Wang
Bohan Wang
Zijie Huang
Carl Yang
Wei-dong Jin
AI4TS
AI4CE
52
0
0
29 Mar 2025
When Graph Neural Networks Meet Dynamic Mode Decomposition
When Graph Neural Networks Meet Dynamic Mode Decomposition
Dai Shi
Lequan Lin
Andi Han
Zhiyong Wang
Yi Guo
Junbin Gao
AI4CE
23
0
0
08 Oct 2024
Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory
Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory
Weichen Zhao
Chenguang Wang
Xinyan Wang
Congying Han
Tiande Guo
Tianshu Yu
38
0
0
23 Feb 2024
RDGCL: Reaction-Diffusion Graph Contrastive Learning for Recommendation
RDGCL: Reaction-Diffusion Graph Contrastive Learning for Recommendation
Jeongwhan Choi
Hyowon Wi
C. Lee
Sung-Bae Cho
Dongha Lee
Noseong Park
DiffM
28
2
0
27 Dec 2023
Graph Convolutions Enrich the Self-Attention in Transformers!
Graph Convolutions Enrich the Self-Attention in Transformers!
Jeongwhan Choi
Hyowon Wi
Jayoung Kim
Yehjin Shin
Kookjin Lee
Nathaniel Trask
Noseong Park
25
3
0
07 Dec 2023
Unifying over-smoothing and over-squashing in graph neural networks: A
  physics informed approach and beyond
Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond
Zhiqi Shao
Dai Shi
Andi Han
Yi Guo
Qianchuan Zhao
Junbin Gao
13
11
0
06 Sep 2023
Graph Neural Controlled Differential Equations for Traffic Forecasting
Graph Neural Controlled Differential Equations for Traffic Forecasting
Jeongwhan Choi
Hwangyong Choi
JeeHyun Hwang
Noseong Park
BDL
AI4TS
85
262
1
07 Dec 2021
Beyond Low-frequency Information in Graph Convolutional Networks
Beyond Low-frequency Information in Graph Convolutional Networks
Deyu Bo
Xiao Wang
C. Shi
Huawei Shen
GNN
87
554
0
04 Jan 2021
Geom-GCN: Geometric Graph Convolutional Networks
Geom-GCN: Geometric Graph Convolutional Networks
Hongbin Pei
Bingzhen Wei
Kevin Chen-Chuan Chang
Yu Lei
Bo Yang
GNN
167
1,058
0
13 Feb 2020
Multi-scale Attributed Node Embedding
Multi-scale Attributed Node Embedding
Benedek Rozemberczki
Carl Allen
Rik Sarkar
GNN
145
828
0
28 Sep 2019
Contextual Stochastic Block Models
Contextual Stochastic Block Models
Y. Deshpande
Andrea Montanari
Elchanan Mossel
S. Sen
98
151
0
23 Jul 2018
Representation Learning on Graphs with Jumping Knowledge Networks
Representation Learning on Graphs with Jumping Knowledge Networks
Keyulu Xu
Chengtao Li
Yonglong Tian
Tomohiro Sonobe
Ken-ichi Kawarabayashi
Stefanie Jegelka
GNN
226
1,935
0
09 Jun 2018
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
1