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Continuous Graph Neural Networks

Continuous Graph Neural Networks

2 December 2019
Louis-Pascal Xhonneux
Meng Qu
Jian Tang
    GNN
ArXivPDFHTML

Papers citing "Continuous Graph Neural Networks"

39 / 39 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
146
1
0
29 Mar 2025
Learning to Decouple Complex Systems
Learning to Decouple Complex Systems
Zihan Zhou
Tianshu Yu
BDL
74
4
0
17 Feb 2025
GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture
GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture
Md. Atik Ahamed
Andrew Cheng
Q. Ye
Q. Cheng
GNN
53
0
0
01 Feb 2025
Community-Aware Temporal Walks: Parameter-Free Representation Learning on Continuous-Time Dynamic Graphs
Community-Aware Temporal Walks: Parameter-Free Representation Learning on Continuous-Time Dynamic Graphs
He Yu
J. Liu
31
0
0
21 Jan 2025
IGNN-Solver: A Graph Neural Solver for Implicit Graph Neural Networks
IGNN-Solver: A Graph Neural Solver for Implicit Graph Neural Networks
Junchao Lin
Zenan Ling
Zhanbo Feng
Feng Zhou
Jingwen Xu
Feng Zhou
Tianqi Hou
Zhenyu Liao
Robert C. Qiu
GNN
AI4CE
52
0
0
11 Oct 2024
Do We Really Need Graph Convolution During Training? Light Post-Training
  Graph-ODE for Efficient Recommendation
Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation
Weizhi Zhang
Liangwei Yang
Zihe Song
Henry Peng Zou
Ke Xu
Liancheng Fang
Philip S. Yu
GNN
34
1
0
26 Jul 2024
Continuous Product Graph Neural Networks
Continuous Product Graph Neural Networks
Aref Einizade
Fragkiskos D. Malliaros
Jhony H. Giraldo
34
1
0
29 May 2024
Convection-Diffusion Equation: A Theoretically Certified Framework for
  Neural Networks
Convection-Diffusion Equation: A Theoretically Certified Framework for Neural Networks
Tangjun Wang
Chenglong Bao
Zuoqiang Shi
DiffM
41
0
0
23 Mar 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
44
0
0
23 Feb 2024
Manifold GCN: Diffusion-based Convolutional Neural Network for Manifold-valued Graphs
Manifold GCN: Diffusion-based Convolutional Neural Network for Manifold-valued Graphs
M. Hanik
Gabriele Steidl
C. V. Tycowicz
GNN
MedIm
36
3
0
25 Jan 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
41
2
0
27 Dec 2023
Signed Graph Neural Ordinary Differential Equation for Modeling
  Continuous-time Dynamics
Signed Graph Neural Ordinary Differential Equation for Modeling Continuous-time Dynamics
Lanlan Chen
K. Wu
Jian Lou
Jing Liu
29
6
0
18 Dec 2023
Graph Neural Ordinary Differential Equations-based method for
  Collaborative Filtering
Graph Neural Ordinary Differential Equations-based method for Collaborative Filtering
Ke Xu
Yuanjie Zhu
Weizhi Zhang
Philip S. Yu
BDL
GNN
21
4
0
21 Nov 2023
How Curvature Enhance the Adaptation Power of Framelet GCNs
How Curvature Enhance the Adaptation Power of Framelet GCNs
Dai Shi
Yi Guo
Zhiqi Shao
Junbin Gao
26
14
0
19 Jul 2023
Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous
  Graph Diffusion Functionals
Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals
Tingting Dan
Jiaqi Ding
Ziquan Wei
S. Kovalsky
Minjeong Kim
Won Hwa Kim
Guorong Wu
DiffM
24
6
0
01 Jul 2023
A Fractional Graph Laplacian Approach to Oversmoothing
A Fractional Graph Laplacian Approach to Oversmoothing
Sohir Maskey
Raffaele Paolino
Aras Bacho
Gitta Kutyniok
24
29
0
22 May 2023
A Survey on Oversmoothing in Graph Neural Networks
A Survey on Oversmoothing in Graph Neural Networks
T. Konstantin Rusch
Michael M. Bronstein
Siddhartha Mishra
26
185
0
20 Mar 2023
TIDE: Time Derivative Diffusion for Deep Learning on Graphs
TIDE: Time Derivative Diffusion for Deep Learning on Graphs
M. Behmanesh
Maximilian Krahn
M. Ovsjanikov
DiffM
GNN
24
9
0
05 Dec 2022
Modular Flows: Differential Molecular Generation
Modular Flows: Differential Molecular Generation
Yogesh Verma
Samuel Kaski
Markus Heinonen
Vikas K. Garg
29
14
0
12 Oct 2022
Generalized energy and gradient flow via graph framelets
Generalized energy and gradient flow via graph framelets
Andi Han
Dai Shi
Zhiqi Shao
Junbin Gao
70
13
0
08 Oct 2022
ACMP: Allen-Cahn Message Passing for Graph Neural Networks with Particle
  Phase Transition
ACMP: Allen-Cahn Message Passing for Graph Neural Networks with Particle Phase Transition
Yuelin Wang
Kai Yi
Xinliang Liu
Yu Guang Wang
Shi Jin
16
33
0
11 Jun 2022
Capturing Graphs with Hypo-Elliptic Diffusions
Capturing Graphs with Hypo-Elliptic Diffusions
Csaba Tóth
Darrick Lee
Celia Hacker
Harald Oberhauser
18
12
0
27 May 2022
Neural Structured Prediction for Inductive Node Classification
Neural Structured Prediction for Inductive Node Classification
Meng Qu
Huiyu Cai
Jian Tang
BDL
GNN
13
18
0
15 Apr 2022
Differential equation and probability inspired graph neural networks for latent variable learning
Differential equation and probability inspired graph neural networks for latent variable learning
Zhuangwei Shi
14
3
0
28 Feb 2022
Graph-Coupled Oscillator Networks
Graph-Coupled Oscillator Networks
T. Konstantin Rusch
B. Chamberlain
J. Rowbottom
S. Mishra
M. Bronstein
31
102
0
04 Feb 2022
Deep Efficient Continuous Manifold Learning for Time Series Modeling
Deep Efficient Continuous Manifold Learning for Time Series Modeling
Seungwoo Jeong
Wonjun Ko
A. Mulyadi
Heung-Il Suk
AI4TS
29
8
0
03 Dec 2021
On the Unreasonable Effectiveness of Feature propagation in Learning on
  Graphs with Missing Node Features
On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features
Emanuele Rossi
Henry Kenlay
Maria I. Gorinova
B. Chamberlain
Xiaowen Dong
M. Bronstein
23
87
0
23 Nov 2021
Climate Modeling with Neural Diffusion Equations
Climate Modeling with Neural Diffusion Equations
JeeHyun Hwang
Jeongwhan Choi
Hwan-Kyu Choi
Kookjin Lee
Dongeun Lee
Noseong Park
DiffM
19
22
0
11 Nov 2021
Quantized Convolutional Neural Networks Through the Lens of Partial
  Differential Equations
Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations
Ido Ben-Yair
Gil Ben Shalom
Moshe Eliasof
Eran Treister
MQ
21
5
0
31 Aug 2021
How Powerful is Graph Convolution for Recommendation?
How Powerful is Graph Convolution for Recommendation?
Yifei Shen
Yongji Wu
Yao Zhang
Caihua Shan
Jun Zhang
Khaled B. Letaief
Dongsheng Li
GNN
28
99
0
17 Aug 2021
Shift-Robust GNNs: Overcoming the Limitations of Localized Graph
  Training Data
Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data
Qi Zhu
Natalia Ponomareva
Jiawei Han
Bryan Perozzi
OOD
22
106
0
02 Aug 2021
Bridging the Gap between Spatial and Spectral Domains: A Unified
  Framework for Graph Neural Networks
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks
Zhiqian Chen
Fanglan Chen
Lei Zhang
Taoran Ji
Kaiqun Fu
Liang Zhao
Feng Chen
Lingfei Wu
Charu C. Aggarwal
Chang-Tien Lu
38
18
0
21 Jul 2021
Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting
Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting
Zheng Fang
Qingqing Long
Guojie Song
Kunqing Xie
AI4TS
17
455
0
24 Jun 2021
GRAND: Graph Neural Diffusion
GRAND: Graph Neural Diffusion
B. Chamberlain
J. Rowbottom
Maria I. Gorinova
Stefan Webb
Emanuele Rossi
M. Bronstein
GNN
24
253
0
21 Jun 2021
Dissecting the Diffusion Process in Linear Graph Convolutional Networks
Dissecting the Diffusion Process in Linear Graph Convolutional Networks
Yifei Wang
Yisen Wang
Jiansheng Yang
Zhouchen Lin
GNN
36
77
0
22 Feb 2021
STEER: Simple Temporal Regularization For Neural ODEs
STEER: Simple Temporal Regularization For Neural ODEs
Arna Ghosh
Harkirat Singh Behl
Emilien Dupont
Philip H. S. Torr
Vinay P. Namboodiri
BDL
AI4TS
24
74
0
18 Jun 2020
Graph Neural Ordinary Differential Equations
Graph Neural Ordinary Differential Equations
Michael Poli
Stefano Massaroli
Junyoung Park
Atsushi Yamashita
Hajime Asama
Jinkyoo Park
AI4CE
42
154
0
18 Nov 2019
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
267
1,945
0
09 Jun 2018
Word Translation Without Parallel Data
Word Translation Without Parallel Data
Alexis Conneau
Guillaume Lample
MarcÁurelio Ranzato
Ludovic Denoyer
Hervé Jégou
174
1,635
0
11 Oct 2017
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