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RandAlign: A Parameter-Free Method for Regularizing Graph Convolutional
  Networks

RandAlign: A Parameter-Free Method for Regularizing Graph Convolutional Networks

15 April 2024
Haimin Zhang
Min Xu
ArXivPDFHTML

Papers citing "RandAlign: A Parameter-Free Method for Regularizing Graph Convolutional Networks"

15 / 15 papers shown
Title
Optimization-Induced Graph Implicit Nonlinear Diffusion
Optimization-Induced Graph Implicit Nonlinear Diffusion
Qi Chen
Yifei Wang
Yisen Wang
Jiansheng Yang
Zhouchen Lin
DiffM
85
32
0
29 Jun 2022
Recipe for a General, Powerful, Scalable Graph Transformer
Recipe for a General, Powerful, Scalable Graph Transformer
Ladislav Rampášek
Mikhail Galkin
Vijay Prakash Dwivedi
Anh Tuan Luu
Guy Wolf
Dominique Beaini
102
556
0
25 May 2022
Rethinking Graph Transformers with Spectral Attention
Rethinking Graph Transformers with Spectral Attention
Devin Kreuzer
Dominique Beaini
William L. Hamilton
Vincent Létourneau
Prudencio Tossou
67
525
0
07 Jun 2021
SSFG: Stochastically Scaling Features and Gradients for Regularizing
  Graph Convolutional Networks
SSFG: Stochastically Scaling Features and Gradients for Regularizing Graph Convolutional Networks
Haimin Zhang
Min Xu
Guoqiang Zhang
Kenta Niwa
32
9
0
20 Feb 2021
Simple and Deep Graph Convolutional Networks
Simple and Deep Graph Convolutional Networks
Ming Chen
Zhewei Wei
Zengfeng Huang
Bolin Ding
Yaliang Li
GNN
82
1,473
0
04 Jul 2020
DeeperGCN: All You Need to Train Deeper GCNs
DeeperGCN: All You Need to Train Deeper GCNs
Guohao Li
Chenxin Xiong
Ali K. Thabet
Guohao Li
GNN
121
438
0
13 Jun 2020
Graph Random Neural Network for Semi-Supervised Learning on Graphs
Graph Random Neural Network for Semi-Supervised Learning on Graphs
Wenzheng Feng
Jie Zhang
Yuxiao Dong
Yu Han
Huanbo Luan
Qian Xu
Qiang Yang
Evgeny Kharlamov
Jie Tang
74
391
0
22 May 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Weihua Hu
Matthias Fey
Marinka Zitnik
Yuxiao Dong
Hongyu Ren
Bowen Liu
Michele Catasta
J. Leskovec
202
2,701
0
02 May 2020
Benchmarking Graph Neural Networks
Benchmarking Graph Neural Networks
Vijay Prakash Dwivedi
Chaitanya K. Joshi
Anh Tuan Luu
T. Laurent
Yoshua Bengio
Xavier Bresson
297
931
0
02 Mar 2020
PairNorm: Tackling Oversmoothing in GNNs
PairNorm: Tackling Oversmoothing in GNNs
Lingxiao Zhao
Leman Akoglu
48
505
0
26 Sep 2019
On the equivalence between graph isomorphism testing and function
  approximation with GNNs
On the equivalence between graph isomorphism testing and function approximation with GNNs
Zhengdao Chen
Soledad Villar
Lei Chen
Joan Bruna
68
278
0
29 May 2019
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Christopher Morris
Martin Ritzert
Matthias Fey
William L. Hamilton
J. E. Lenssen
Gaurav Rattan
Martin Grohe
GNN
136
1,625
0
04 Oct 2018
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
173
7,554
0
01 Oct 2018
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
319
19,991
0
30 Oct 2017
Spectral Networks and Locally Connected Networks on Graphs
Spectral Networks and Locally Connected Networks on Graphs
Joan Bruna
Wojciech Zaremba
Arthur Szlam
Yann LeCun
GNN
141
4,856
0
21 Dec 2013
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