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Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph
  Kernels

Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels

30 May 2019
S. Du
Kangcheng Hou
Barnabás Póczós
Ruslan Salakhutdinov
Ruosong Wang
Keyulu Xu
ArXivPDFHTML

Papers citing "Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels"

50 / 56 papers shown
Title
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
Graph Condensation: A Survey
Graph Condensation: A Survey
Xin Gao
Junliang Yu
Wei Jiang
Tong Chen
Wentao Zhang
Hongzhi Yin
DD
88
19
0
28 Jan 2025
Peer-to-Peer Learning Dynamics of Wide Neural Networks
Peer-to-Peer Learning Dynamics of Wide Neural Networks
Shreyas Chaudhari
Srinivasa Pranav
Emile Anand
José M. F. Moura
37
3
0
23 Sep 2024
Equivariant Neural Tangent Kernels
Equivariant Neural Tangent Kernels
Philipp Misof
Pan Kessel
Jan E. Gerken
58
0
0
10 Jun 2024
Descriptive Kernel Convolution Network with Improved Random Walk Kernel
Descriptive Kernel Convolution Network with Improved Random Walk Kernel
Meng-Chieh Lee
Lingxiao Zhao
L. Akoglu
21
3
0
08 Feb 2024
Expectation-Complete Graph Representations with Homomorphisms
Expectation-Complete Graph Representations with Homomorphisms
Pascal Welke
Maximilian Thiessen
Fabian Jogl
Thomas Gärtner
18
6
0
09 Jun 2023
LON-GNN: Spectral GNNs with Learnable Orthonormal Basis
LON-GNN: Spectral GNNs with Learnable Orthonormal Basis
Qian Tao
Zhen Wang
Wenyuan Yu
Yaliang Li
Zhewei Wei
27
5
0
24 Mar 2023
Technical report: Graph Neural Networks go Grammatical
Technical report: Graph Neural Networks go Grammatical
Jason Piquenot
Aldo Moscatelli
Maxime Bérar
Pierre Héroux
R. Raveaux
Jean-Yves Ramel
Sébastien Adam
25
1
0
02 Mar 2023
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on
  Graph Diffusion
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion
Haotian Ju
Dongyue Li
Aneesh Sharma
Hongyang R. Zhang
31
40
0
09 Feb 2023
Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised
  Node Classification
Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification
Sonny Achten
F. Tonin
Panagiotis Patrinos
Johan A. K. Suykens
42
4
0
31 Jan 2023
A Simple Algorithm For Scaling Up Kernel Methods
A Simple Algorithm For Scaling Up Kernel Methods
Tengyu Xu
Bryan T. Kelly
Semyon Malamud
11
0
0
26 Jan 2023
Understanding and Improving Deep Graph Neural Networks: A Probabilistic
  Graphical Model Perspective
Understanding and Improving Deep Graph Neural Networks: A Probabilistic Graphical Model Perspective
Jiayuan Chen
Xiang Zhang
Yinfei Xu
Tianli Zhao
Renjie Xie
Wei Xu
GNN
BDL
21
0
0
25 Jan 2023
Graph Neural Networks are Inherently Good Generalizers: Insights by
  Bridging GNNs and MLPs
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs
Chenxiao Yang
Qitian Wu
Jiahua Wang
Junchi Yan
AI4CE
19
51
0
18 Dec 2022
FedMT: Federated Learning with Mixed-type Labels
FedMT: Federated Learning with Mixed-type Labels
Qiong Zhang
Jing Peng
Xin Zhang
A. Talhouk
Gang Niu
Xiaoxiao Li
FedML
51
0
0
05 Oct 2022
Provably expressive temporal graph networks
Provably expressive temporal graph networks
Amauri Souza
Diego Mesquita
Samuel Kaski
Vikas K. Garg
89
54
0
29 Sep 2022
Graph Neural Network Bandits
Graph Neural Network Bandits
Parnian Kassraie
Andreas Krause
Ilija Bogunovic
26
11
0
13 Jul 2022
Bounding the Width of Neural Networks via Coupled Initialization -- A
  Worst Case Analysis
Bounding the Width of Neural Networks via Coupled Initialization -- A Worst Case Analysis
Alexander Munteanu
Simon Omlor
Zhao-quan Song
David P. Woodruff
27
15
0
26 Jun 2022
Fast Finite Width Neural Tangent Kernel
Fast Finite Width Neural Tangent Kernel
Roman Novak
Jascha Narain Sohl-Dickstein
S. Schoenholz
AAML
20
53
0
17 Jun 2022
Graph-level Neural Networks: Current Progress and Future Directions
Graph-level Neural Networks: Current Progress and Future Directions
Ge Zhang
Jia Wu
Jian Yang
Shan Xue
Wenbin Hu
Chuan Zhou
Hao Peng
Quan.Z Sheng
Charu C. Aggarwal
GNN
AI4CE
38
0
0
31 May 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks
NeuralEF: Deconstructing Kernels by Deep Neural Networks
Zhijie Deng
Jiaxin Shi
Jun Zhu
16
18
0
30 Apr 2022
Theory of Graph Neural Networks: Representation and Learning
Theory of Graph Neural Networks: Representation and Learning
Stefanie Jegelka
GNN
AI4CE
33
68
0
16 Apr 2022
Generalization Through The Lens Of Leave-One-Out Error
Generalization Through The Lens Of Leave-One-Out Error
Gregor Bachmann
Thomas Hofmann
Aurélien Lucchi
46
7
0
07 Mar 2022
Demystify Optimization and Generalization of Over-parameterized
  PAC-Bayesian Learning
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning
Wei Huang
Chunrui Liu
Yilan Chen
Tianyu Liu
R. Xu
BDL
MLT
19
2
0
04 Feb 2022
Towards Quantum Graph Neural Networks: An Ego-Graph Learning Approach
Towards Quantum Graph Neural Networks: An Ego-Graph Learning Approach
Xing Ai
Zhihong Zhang
Luzhe Sun
Junchi Yan
Edwin R. Hancock
GNN
39
11
0
13 Jan 2022
Rethinking Influence Functions of Neural Networks in the
  Over-parameterized Regime
Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime
Rui Zhang
Shihua Zhang
TDI
19
21
0
15 Dec 2021
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural
  Networks
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks
P. Esser
L. C. Vankadara
D. Ghoshdastidar
28
53
0
07 Dec 2021
Fast Graph Neural Tangent Kernel via Kronecker Sketching
Fast Graph Neural Tangent Kernel via Kronecker Sketching
Shunhua Jiang
Yunze Man
Zhao-quan Song
Zheng Yu
Danyang Zhuo
26
6
0
04 Dec 2021
On the Equivalence between Neural Network and Support Vector Machine
On the Equivalence between Neural Network and Support Vector Machine
Yilan Chen
Wei Huang
Lam M. Nguyen
Tsui-Wei Weng
AAML
17
18
0
11 Nov 2021
Learning on Random Balls is Sufficient for Estimating (Some) Graph
  Parameters
Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters
Takanori Maehara
Hoang NT
41
2
0
05 Nov 2021
On Provable Benefits of Depth in Training Graph Convolutional Networks
On Provable Benefits of Depth in Training Graph Convolutional Networks
Weilin Cong
M. Ramezani
M. Mahdavi
24
73
0
28 Oct 2021
Imitating Deep Learning Dynamics via Locally Elastic Stochastic
  Differential Equations
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations
Jiayao Zhang
Hua Wang
Weijie J. Su
32
7
0
11 Oct 2021
New Insights into Graph Convolutional Networks using Neural Tangent
  Kernels
New Insights into Graph Convolutional Networks using Neural Tangent Kernels
Mahalakshmi Sabanayagam
P. Esser
D. Ghoshdastidar
21
6
0
08 Oct 2021
Subgraph Federated Learning with Missing Neighbor Generation
Subgraph Federated Learning with Missing Neighbor Generation
Ke Zhang
Carl Yang
Xiaoxiao Li
Lichao Sun
S. Yiu
FedML
19
163
0
25 Jun 2021
Learning to Pool in Graph Neural Networks for Extrapolation
Learning to Pool in Graph Neural Networks for Extrapolation
Jihoon Ko
Taehyung Kwon
Kijung Shin
Juho Lee
21
6
0
11 Jun 2021
GraphiT: Encoding Graph Structure in Transformers
GraphiT: Encoding Graph Structure in Transformers
Grégoire Mialon
Dexiong Chen
Margot Selosse
Julien Mairal
20
164
0
10 Jun 2021
Unsupervised Shape Completion via Deep Prior in the Neural Tangent
  Kernel Perspective
Unsupervised Shape Completion via Deep Prior in the Neural Tangent Kernel Perspective
Lei Chu
Hao Pan
Wenping Wang
3DPC
32
11
0
19 Apr 2021
Graph Neural Networks: Taxonomy, Advances and Trends
Graph Neural Networks: Taxonomy, Advances and Trends
Yu Zhou
Haixia Zheng
Xin Huang
Shufeng Hao
Dengao Li
Jumin Zhao
AI4TS
25
115
0
16 Dec 2020
Graph Kernels: State-of-the-Art and Future Challenges
Graph Kernels: State-of-the-Art and Future Challenges
Karsten M. Borgwardt
Elisabetta Ghisu
Felipe Llinares-López
Leslie O’Bray
Bastian Alexander Rieck
AI4TS
31
101
0
07 Nov 2020
From Local Structures to Size Generalization in Graph Neural Networks
From Local Structures to Size Generalization in Graph Neural Networks
Gilad Yehudai
Ethan Fetaya
E. Meirom
Gal Chechik
Haggai Maron
GNN
AI4CE
169
123
0
17 Oct 2020
Information Obfuscation of Graph Neural Networks
Information Obfuscation of Graph Neural Networks
Peiyuan Liao
Han Zhao
Keyulu Xu
Tommi Jaakkola
Geoffrey J. Gordon
Stefanie Jegelka
Ruslan Salakhutdinov
AAML
20
34
0
28 Sep 2020
GraphNorm: A Principled Approach to Accelerating Graph Neural Network
  Training
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
Tianle Cai
Shengjie Luo
Keyulu Xu
Di He
Tie-Yan Liu
Liwei Wang
GNN
23
158
0
07 Sep 2020
Tensor Programs II: Neural Tangent Kernel for Any Architecture
Tensor Programs II: Neural Tangent Kernel for Any Architecture
Greg Yang
43
134
0
25 Jun 2020
Improving Graph Neural Network Expressivity via Subgraph Isomorphism
  Counting
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting
Giorgos Bouritsas
Fabrizio Frasca
S. Zafeiriou
M. Bronstein
46
424
0
16 Jun 2020
Optimization and Generalization Analysis of Transduction through
  Gradient Boosting and Application to Multi-scale Graph Neural Networks
Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks
Kenta Oono
Taiji Suzuki
AI4CE
37
31
0
15 Jun 2020
Adversarial Attack on Hierarchical Graph Pooling Neural Networks
Adversarial Attack on Hierarchical Graph Pooling Neural Networks
Haoteng Tang
Guixiang Ma
Yurong Chen
Lei Guo
Wei Wang
Bo Zeng
Liang Zhan
AAML
26
28
0
23 May 2020
Random Features for Kernel Approximation: A Survey on Algorithms,
  Theory, and Beyond
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond
Fanghui Liu
Xiaolin Huang
Yudong Chen
Johan A. K. Suykens
BDL
34
172
0
23 Apr 2020
Generalization and Representational Limits of Graph Neural Networks
Generalization and Representational Limits of Graph Neural Networks
Vikas K. Garg
Stefanie Jegelka
Tommi Jaakkola
GNN
26
303
0
14 Feb 2020
On the infinite width limit of neural networks with a standard
  parameterization
On the infinite width limit of neural networks with a standard parameterization
Jascha Narain Sohl-Dickstein
Roman Novak
S. Schoenholz
Jaehoon Lee
19
47
0
21 Jan 2020
Deep Graph Similarity Learning: A Survey
Deep Graph Similarity Learning: A Survey
Guixiang Ma
Nesreen Ahmed
Theodore L. Willke
Philip S. Yu
GNN
21
77
0
25 Dec 2019
Neural Tangents: Fast and Easy Infinite Neural Networks in Python
Neural Tangents: Fast and Easy Infinite Neural Networks in Python
Roman Novak
Lechao Xiao
Jiri Hron
Jaehoon Lee
Alexander A. Alemi
Jascha Narain Sohl-Dickstein
S. Schoenholz
27
224
0
05 Dec 2019
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