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PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by
  Partial Differential Equations

PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations

4 August 2021
Moshe Eliasof
E. Haber
Eran Treister
    GNN
    AI4CE
ArXivPDFHTML

Papers citing "PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations"

27 / 27 papers shown
Title
Resolving Oversmoothing with Opinion Dissensus
Resolving Oversmoothing with Opinion Dissensus
Keqin Wang
Yulong Yang
Ishan Saha
Christine Allen-Blanchette
60
1
0
31 Jan 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
Learning Regularization for Graph Inverse Problems
Learning Regularization for Graph Inverse Problems
Moshe Eliasof
Md Shahriar Rahim Siddiqui
Carola-Bibiane Schönlieb
Eldad Haber
GNN
34
0
0
19 Aug 2024
Graph Neural Reaction Diffusion Models
Graph Neural Reaction Diffusion Models
Moshe Eliasof
Eldad Haber
Eran Treister
DiffM
AI4CE
35
2
0
16 Jun 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
46
0
0
23 Mar 2024
Simplified PCNet with Robustness
Simplified PCNet with Robustness
Bingheng Li
Xuanting Xie
Haoxiang Lei
Ruiyi Fang
Zhao Kang
37
5
0
06 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
PC-Conv: Unifying Homophily and Heterophily with Two-fold Filtering
PC-Conv: Unifying Homophily and Heterophily with Two-fold Filtering
Bingheng Li
Erlin Pan
Zhao Kang
21
31
0
22 Dec 2023
Dirichlet Energy Enhancement of Graph Neural Networks by Framelet
  Augmentation
Dirichlet Energy Enhancement of Graph Neural Networks by Framelet Augmentation
Jialin Chen
Yuelin Wang
Cristian Bodnar
Rex Ying
Pietro Lió
Yu Guang Wang
29
10
0
09 Nov 2023
QDC: Quantum Diffusion Convolution Kernels on Graphs
QDC: Quantum Diffusion Convolution Kernels on Graphs
Thomas Markovich
GNN
24
3
0
20 Jul 2023
TransformerG2G: Adaptive time-stepping for learning temporal graph
  embeddings using transformers
TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformers
Alan John Varghese
Aniruddha Bora
Mengjia Xu
George Karniadakis
36
5
0
05 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
PDE+: Enhancing Generalization via PDE with Adaptive Distributional
  Diffusion
PDE+: Enhancing Generalization via PDE with Adaptive Distributional Diffusion
Yige Yuan
Bingbing Xu
Bo Lin
Liang Hou
Fei Sun
Huawei Shen
Xueqi Cheng
DiffM
26
4
0
25 May 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
AGNN: Alternating Graph-Regularized Neural Networks to Alleviate
  Over-Smoothing
AGNN: Alternating Graph-Regularized Neural Networks to Alleviate Over-Smoothing
Zhaoliang Chen
Zhihao Wu
Zhe-Hui Lin
Shiping Wang
Claudia Plant
Wenzhong Guo
29
18
0
14 Apr 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
Learning PDE Solution Operator for Continuous Modeling of Time-Series
Learning PDE Solution Operator for Continuous Modeling of Time-Series
Yesom Park
Jaemoo Choi
Changyeon Yoon
Changhoon Song
Myung-joo Kang
AI4TS
AI4CE
27
3
0
02 Feb 2023
Changes from Classical Statistics to Modern Statistics and Data Science
Changes from Classical Statistics to Modern Statistics and Data Science
Kai Zhang
Shan-Yu Liu
M. Xiong
31
0
0
30 Oct 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
72
13
0
08 Oct 2022
Estimating a potential without the agony of the partition function
Estimating a potential without the agony of the partition function
E. Haber
Moshe Eliasof
L. Tenorio
33
2
0
19 Aug 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
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
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
24
5
0
31 Aug 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
169
1,078
0
13 Feb 2020
Multi-scale Attributed Node Embedding
Multi-scale Attributed Node Embedding
Benedek Rozemberczki
Carl Allen
Rik Sarkar
GNN
148
837
0
28 Sep 2019
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
251
1,811
0
25 Nov 2016
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