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Simplifying Graph Convolutional Networks

Simplifying Graph Convolutional Networks

19 February 2019
Felix Wu
Tianyi Zhang
Amauri Souza
Christopher Fifty
Tao Yu
Kilian Q. Weinberger
    GNN
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Papers citing "Simplifying Graph Convolutional Networks"

41 / 1,391 papers shown
Title
GraphZoom: A multi-level spectral approach for accurate and scalable
  graph embedding
GraphZoom: A multi-level spectral approach for accurate and scalable graph embedding
Chenhui Deng
Zhiqiang Zhao
Yongyu Wang
Zhiru Zhang
Zhuo Feng
32
105
0
06 Oct 2019
Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks
Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks
Guillaume Salha-Galvan
Romain Hennequin
Michalis Vazirgiannis
GNN
BDL
32
50
0
02 Oct 2019
Graph Residual Flow for Molecular Graph Generation
Graph Residual Flow for Molecular Graph Generation
Shion Honda
Hirotaka Akita
Katsuhiko Ishiguro
Toshiki Nakanishi
Kenta Oono
18
42
0
30 Sep 2019
Multi-scale Attributed Node Embedding
Multi-scale Attributed Node Embedding
Benedek Rozemberczki
Carl Allen
Rik Sarkar
GNN
148
837
0
28 Sep 2019
Graph-Preserving Grid Layout: A Simple Graph Drawing Method for Graph
  Classification using CNNs
Graph-Preserving Grid Layout: A Simple Graph Drawing Method for Graph Classification using CNNs
Yecheng Lyu
Xinming Huang
Ziming Zhang
29
0
0
26 Sep 2019
PairNorm: Tackling Oversmoothing in GNNs
PairNorm: Tackling Oversmoothing in GNNs
Lingxiao Zhao
Leman Akoglu
16
501
0
26 Sep 2019
PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation
  Invariant Set Functions
PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions
Shupeng Gui
Xiangliang Zhang
Pan Zhong
Shuang Qiu
Mingrui Wu
Jieping Ye
Zhengdao Wang
Ji Liu
27
15
0
25 Sep 2019
Layerwise Relevance Visualization in Convolutional Text Graph
  Classifiers
Layerwise Relevance Visualization in Convolutional Text Graph Classifiers
Robert Schwarzenberg
Marc Hübner
David Harbecke
Christoph Alt
Leonhard Hennig
FAtt
GNN
12
69
0
24 Sep 2019
Spatial Graph Convolutional Networks
Spatial Graph Convolutional Networks
Tomasz Danel
Przemysław Spurek
Jacek Tabor
Marek Śmieja
Lukasz Struski
Agnieszka Słowik
Lukasz Maziarka
GNN
32
10
0
11 Sep 2019
Auto-GNN: Neural Architecture Search of Graph Neural Networks
Auto-GNN: Neural Architecture Search of Graph Neural Networks
Kaixiong Zhou
Qingquan Song
Xiao Huang
Xia Hu
GNN
61
178
0
07 Sep 2019
Parallel Computation of Graph Embeddings
Parallel Computation of Graph Embeddings
Chi Thang Duong
Hongzhi Yin
Thanh Dat Hoang
Truong Giang Le Ba
Matthias Weidlich
Quoc Viet Hung Nguyen
Karl Aberer
GNN
17
2
0
06 Sep 2019
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph
  Neural Networks
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
Minjie Wang
Da Zheng
Zihao Ye
Quan Gan
Mufei Li
...
J. Zhao
Haotong Zhang
Alex Smola
Jinyang Li
Zheng-Wei Zhang
AI4CE
GNN
206
747
0
03 Sep 2019
EnGN: A High-Throughput and Energy-Efficient Accelerator for Large Graph
  Neural Networks
EnGN: A High-Throughput and Energy-Efficient Accelerator for Large Graph Neural Networks
Shengwen Liang
Ying Wang
Cheng Liu
Lei He
Huawei Li
Xiaowei Li
GNN
14
132
0
31 Aug 2019
Transferring Robustness for Graph Neural Network Against Poisoning
  Attacks
Transferring Robustness for Graph Neural Network Against Poisoning Attacks
Xianfeng Tang
Yandong Li
Yiwei Sun
Huaxiu Yao
P. Mitra
Suhang Wang
OOD
AAML
27
181
0
20 Aug 2019
Neural Dynamics on Complex Networks
Neural Dynamics on Complex Networks
Chengxi Zang
Fei Wang
AI4CE
35
68
0
18 Aug 2019
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
Ke Sun
Zhanxing Zhu
Zhouchen Lin
GNN
33
80
0
14 Aug 2019
A Restricted Black-box Adversarial Framework Towards Attacking Graph
  Embedding Models
A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models
Heng Chang
Yu Rong
Tingyang Xu
Wenbing Huang
Honglei Zhang
Peng Cui
Wenwu Zhu
Junzhou Huang
AAML
13
151
0
04 Aug 2019
EEG-Based Emotion Recognition Using Regularized Graph Neural Networks
EEG-Based Emotion Recognition Using Regularized Graph Neural Networks
Peixiang Zhong
Di Wang
Chunyan Miao
39
513
0
18 Jul 2019
Fast Haar Transforms for Graph Neural Networks
Fast Haar Transforms for Graph Neural Networks
Ming Li
Zheng Ma
Yu Guang Wang
Xiaosheng Zhuang
33
74
0
10 Jul 2019
Label-Aware Graph Convolutional Networks
Label-Aware Graph Convolutional Networks
Hao Chen
Yue Xu
Lu Wang
Dijun Luo
Wenbing Huang
Senzhang Wang
Peng He
Zhoujun Li
18
8
0
10 Jul 2019
Graph Star Net for Generalized Multi-Task Learning
Graph Star Net for Generalized Multi-Task Learning
H. Lu
Seth H. Huang
Tian Ye
Xiuyan Guo
GNN
33
46
0
21 Jun 2019
Redundancy-Free Computation Graphs for Graph Neural Networks
Redundancy-Free Computation Graphs for Graph Neural Networks
Zhihao Jia
Sina Lin
Rex Ying
Jiaxuan You
J. Leskovec
Alexander Aiken
GNN
31
11
0
09 Jun 2019
Quantifying the Alignment of Graph and Features in Deep Learning
Quantifying the Alignment of Graph and Features in Deep Learning
Yifan Qian
P. Expert
Tom Rieu
P. Panzarasa
Mauricio Barahona
23
18
0
30 May 2019
Graph Neural Networks Exponentially Lose Expressive Power for Node
  Classification
Graph Neural Networks Exponentially Lose Expressive Power for Node Classification
Kenta Oono
Taiji Suzuki
GNN
32
27
0
27 May 2019
Power up! Robust Graph Convolutional Network via Graph Powering
Power up! Robust Graph Convolutional Network via Graph Powering
Ming Jin
Heng Chang
Wenwu Zhu
Somayeh Sojoudi
AAML
GNN
19
27
0
24 May 2019
Meta-GNN: On Few-shot Node Classification in Graph Meta-learning
Meta-GNN: On Few-shot Node Classification in Graph Meta-learning
Fan Zhou
Chengtai Cao
Kunpeng Zhang
Goce Trajcevski
Ting Zhong
Ji Geng
16
226
0
23 May 2019
Gravity-Inspired Graph Autoencoders for Directed Link Prediction
Gravity-Inspired Graph Autoencoders for Directed Link Prediction
Guillaume Salha-Galvan
Stratis Limnios
Romain Hennequin
Viet-Anh Tran
Michalis Vazirgiannis
GNN
CML
33
95
0
23 May 2019
Revisiting Graph Neural Networks: All We Have is Low-Pass Filters
Revisiting Graph Neural Networks: All We Have is Low-Pass Filters
Hoang NT
Takanori Maehara
GNN
22
420
0
23 May 2019
Are Powerful Graph Neural Nets Necessary? A Dissection on Graph
  Classification
Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification
Ting-Li Chen
Song Bian
Yizhou Sun
11
88
0
11 May 2019
PAN: Path Integral Based Convolution for Deep Graph Neural Networks
PAN: Path Integral Based Convolution for Deep Graph Neural Networks
Zheng Ma
Ming Li
Yuguang Wang
GNN
22
24
0
24 Apr 2019
Simple BERT Models for Relation Extraction and Semantic Role Labeling
Simple BERT Models for Relation Extraction and Semantic Role Labeling
Peng Shi
Jimmy J. Lin
VLM
8
442
0
10 Apr 2019
Fisher-Bures Adversary Graph Convolutional Networks
Fisher-Bures Adversary Graph Convolutional Networks
Ke Sun
Piotr Koniusz
Zhen Wang
GNN
21
34
0
11 Mar 2019
Fast Graph Representation Learning with PyTorch Geometric
Fast Graph Representation Learning with PyTorch Geometric
Matthias Fey
J. E. Lenssen
3DH
GNN
3DPC
68
4,235
0
06 Mar 2019
Graph Neural Networks with convolutional ARMA filters
Graph Neural Networks with convolutional ARMA filters
F. Bianchi
Daniele Grattarola
L. Livi
Cesare Alippi
GNN
25
387
0
05 Jan 2019
Adversarial Attack and Defense on Graph Data: A Survey
Adversarial Attack and Defense on Graph Data: A Survey
Lichao Sun
Yingtong Dou
Carl Yang
Ji Wang
Yixin Liu
Philip S. Yu
Lifang He
Yangqiu Song
GNN
AAML
18
273
0
26 Dec 2018
Graph Neural Networks: A Review of Methods and Applications
Graph Neural Networks: A Review of Methods and Applications
Jie Zhou
Ganqu Cui
Shengding Hu
Zhengyan Zhang
Cheng Yang
Zhiyuan Liu
Lifeng Wang
Changcheng Li
Maosong Sun
AI4CE
GNN
28
5,400
0
20 Dec 2018
Deep Learning on Graphs: A Survey
Deep Learning on Graphs: A Survey
Ziwei Zhang
Peng Cui
Wenwu Zhu
GNN
51
1,321
0
11 Dec 2018
ExpandNets: Linear Over-parameterization to Train Compact Convolutional
  Networks
ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks
Shuxuan Guo
J. Álvarez
Mathieu Salzmann
21
77
0
26 Nov 2018
A simple yet effective baseline for non-attributed graph classification
A simple yet effective baseline for non-attributed graph classification
Chen Cai
Yusu Wang
19
32
0
08 Nov 2018
Every Node Counts: Self-Ensembling Graph Convolutional Networks for
  Semi-Supervised Learning
Every Node Counts: Self-Ensembling Graph Convolutional Networks for Semi-Supervised Learning
Yawei Luo
T. Guan
Junqing Yu
Ping Liu
Yi Yang
SSL
GNN
22
32
0
26 Sep 2018
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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