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Aggregation Buffer: Revisiting DropEdge with a New Parameter Block

Aggregation Buffer: Revisiting DropEdge with a New Parameter Block

27 May 2025
Dooho Lee
Myeong Kong
Sagad Hamid
Cheonwoo Lee
Jaemin Yoo
ArXiv (abs)PDFHTML

Papers citing "Aggregation Buffer: Revisiting DropEdge with a New Parameter Block"

34 / 34 papers shown
Title
Classic GNNs are Strong Baselines: Reassessing GNNs for Node
  Classification
Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification
Yuankai Luo
Lei Shi
Xiao-Ming Wu
83
31
0
13 Jun 2024
Understanding Heterophily for Graph Neural Networks
Understanding Heterophily for Graph Neural Networks
Junfu Wang
Yuanfang Guo
Liang Yang
Yun-an Wang
73
15
0
17 Jan 2024
GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via
  Test-time Augmentation
GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation
Mingxuan Ju
Tong Zhao
Wenhao Yu
Neil Shah
Yanfang Ye
75
16
0
01 Oct 2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size
  Fit All?
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
Haitao Mao
Zhikai Chen
Wei Jin
Haoyu Han
Yao Ma
Tong Zhao
Neil Shah
Jiliang Tang
87
36
0
02 Jun 2023
A critical look at the evaluation of GNNs under heterophily: Are we
  really making progress?
A critical look at the evaluation of GNNs under heterophily: Are we really making progress?
Oleg Platonov
Denis Kuznedelev
Michael Diskin
Artem Babenko
Liudmila Prokhorenkova
90
222
0
22 Feb 2023
On Generalized Degree Fairness in Graph Neural Networks
On Generalized Degree Fairness in Graph Neural Networks
Zemin Liu
Trung-Kien Nguyen
Yuan Fang
61
28
0
08 Feb 2023
What's Behind the Mask: Understanding Masked Graph Modeling for Graph
  Autoencoders
What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders
Jintang Li
Ruofan Wu
Wangbin Sun
Liang Chen
Sheng Tian
Liang Zhu
Changhua Meng
Zibin Zheng
Weiqiang Wang
SSL
85
92
0
20 May 2022
DropMessage: Unifying Random Dropping for Graph Neural Networks
DropMessage: Unifying Random Dropping for Graph Neural Networks
Taoran Fang
Zhiqing Xiao
Chunping Wang
Jiarong Xu
Xuan Yang
Yang Yang
45
51
0
21 Apr 2022
Token Dropping for Efficient BERT Pretraining
Token Dropping for Efficient BERT Pretraining
Le Hou
Richard Yuanzhe Pang
Dinesh Manocha
Yuexin Wu
Xinying Song
Xiaodan Song
Denny Zhou
74
45
0
24 Mar 2022
Cold Brew: Distilling Graph Node Representations with Incomplete or
  Missing Neighborhoods
Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods
Wenqing Zheng
Edward W. Huang
Nikhil S. Rao
S. Katariya
Zhangyang Wang
Karthik Subbian
78
66
0
08 Nov 2021
Graph-less Neural Networks: Teaching Old MLPs New Tricks via
  Distillation
Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation
Shichang Zhang
Yozen Liu
Yizhou Sun
Neil Shah
88
185
0
17 Oct 2021
From Canonical Correlation Analysis to Self-supervised Graph Neural
  Networks
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks
Hengrui Zhang
Qitian Wu
Junchi Yan
David Wipf
Philip S. Yu
SSL
67
221
0
23 Jun 2021
How Attentive are Graph Attention Networks?
How Attentive are Graph Attention Networks?
Shaked Brody
Uri Alon
Eran Yahav
GNN
123
1,085
0
30 May 2021
Graph-based Semi-supervised Learning: A Comprehensive Review
Graph-based Semi-supervised Learning: A Comprehensive Review
Zixing Song
Xiangli Yang
Zenglin Xu
Irwin King
149
205
0
26 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
124
1,496
0
04 Jul 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
102
394
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
309
2,746
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
490
950
0
02 Mar 2020
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
324
1,123
0
13 Feb 2020
DropEdge: Towards Deep Graph Convolutional Networks on Node
  Classification
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
Yu Rong
Wenbing Huang
Tingyang Xu
Junzhou Huang
110
1,346
0
25 Jul 2019
GraphSAINT: Graph Sampling Based Inductive Learning Method
GraphSAINT: Graph Sampling Based Inductive Learning Method
Hanqing Zeng
Hongkuan Zhou
Ajitesh Srivastava
Rajgopal Kannan
Viktor Prasanna
GNN
137
968
0
10 Jul 2019
Strategies for Pre-training Graph Neural Networks
Strategies for Pre-training Graph Neural Networks
Weihua Hu
Bowen Liu
Joseph Gomes
Marinka Zitnik
Percy Liang
Vijay S. Pande
J. Leskovec
SSLAI4CE
118
1,415
0
29 May 2019
Simplifying Graph Convolutional Networks
Simplifying Graph Convolutional Networks
Felix Wu
Tianyi Zhang
Amauri Souza
Christopher Fifty
Tao Yu
Kilian Q. Weinberger
GNN
248
3,182
0
19 Feb 2019
Pitfalls of Graph Neural Network Evaluation
Pitfalls of Graph Neural Network Evaluation
Oleksandr Shchur
Maximilian Mumme
Aleksandar Bojchevski
Stephan Günnemann
GNN
168
1,365
0
14 Nov 2018
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
257
7,695
0
01 Oct 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
518
1,990
0
09 Jun 2018
Graph Convolutional Neural Networks for Web-Scale Recommender Systems
Graph Convolutional Neural Networks for Web-Scale Recommender Systems
Rex Ying
Ruining He
Kaifeng Chen
Pong Eksombatchai
William L. Hamilton
J. Leskovec
GNNBDL
266
3,550
0
06 Jun 2018
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
481
20,233
0
30 Oct 2017
Improved Regularization of Convolutional Neural Networks with Cutout
Improved Regularization of Convolutional Neural Networks with Cutout
Terrance Devries
Graham W. Taylor
129
3,774
0
15 Aug 2017
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large Graphs
William L. Hamilton
Z. Ying
J. Leskovec
514
15,319
0
07 Jun 2017
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
598
7,488
0
04 Apr 2017
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNNSSL
662
29,156
0
09 Sep 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,426
0
10 Dec 2015
Distilling the Knowledge in a Neural Network
Distilling the Knowledge in a Neural Network
Geoffrey E. Hinton
Oriol Vinyals
J. Dean
FedML
364
19,733
0
09 Mar 2015
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