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NCGNN: Node-Level Capsule Graph Neural Network for Semisupervised
  Classification
v1v2 (latest)

NCGNN: Node-Level Capsule Graph Neural Network for Semisupervised Classification

7 December 2020
Rui Yang
Wenrui Dai
Chenglin Li
Junni Zou
H. Xiong
ArXiv (abs)PDFHTML

Papers citing "NCGNN: Node-Level Capsule Graph Neural Network for Semisupervised Classification"

50 / 56 papers shown
Title
Robust Counterfactual Explanations on Graph Neural Networks
Robust Counterfactual Explanations on Graph Neural Networks
Mohit Bajaj
Lingyang Chu
Zihui Xue
J. Pei
Lanjun Wang
P. C. Lam
Yong Zhang
OOD
166
100
0
08 Jul 2021
Generative Causal Explanations for Graph Neural Networks
Generative Causal Explanations for Graph Neural Networks
Wanyu Lin
Hao Lan
Baochun Li
CML
63
178
0
14 Apr 2021
On Explainability of Graph Neural Networks via Subgraph Explorations
On Explainability of Graph Neural Networks via Subgraph Explorations
Hao Yuan
Haiyang Yu
Jie Wang
Kang Li
Shuiwang Ji
FAtt
83
395
0
09 Feb 2021
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
Ana Lucic
Maartje ter Hoeve
Gabriele Tolomei
Maarten de Rijke
Fabrizio Silvestri
204
146
0
05 Feb 2021
Hierarchical Graph Capsule Network
Hierarchical Graph Capsule Network
Jinyu Yang
P. Zhao
Yu Rong
Chao-chao Yan
Chunyuan Li
Hehuan Ma
Junzhou Huang
67
31
0
16 Dec 2020
Parameterized Explainer for Graph Neural Network
Parameterized Explainer for Graph Neural Network
Dongsheng Luo
Wei Cheng
Dongkuan Xu
Wenchao Yu
Bo Zong
Haifeng Chen
Xiang Zhang
149
563
0
09 Nov 2020
PGM-Explainer: Probabilistic Graphical Model Explanations for Graph
  Neural Networks
PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks
Minh Nhat Vu
My T. Thai
BDL
91
339
0
12 Oct 2020
Towards Deeper Graph Neural Networks
Towards Deeper Graph Neural Networks
Meng Liu
Hongyang Gao
Shuiwang Ji
GNNAI4CE
112
609
0
18 Jul 2020
Simple and Deep Graph Convolutional Networks
Simple and Deep Graph Convolutional Networks
Ming Chen
Zhewei Wei
Zengfeng Huang
Bolin Ding
Yaliang Li
GNN
133
1,505
0
04 Jul 2020
Scaling Graph Neural Networks with Approximate PageRank
Scaling Graph Neural Networks with Approximate PageRank
Aleksandar Bojchevski
Johannes Klicpera
Bryan Perozzi
Amol Kapoor
Martin J. Blais
Benedek Rozemberczki
Michal Lukasik
Stephan Günnemann
GNN
171
374
0
03 Jul 2020
Towards Deeper Graph Neural Networks with Differentiable Group
  Normalization
Towards Deeper Graph Neural Networks with Differentiable Group Normalization
Kaixiong Zhou
Xiao Huang
Yuening Li
Daochen Zha
Rui Chen
Helen Zhou
142
205
0
12 Jun 2020
Bayesian Graph Neural Networks with Adaptive Connection Sampling
Bayesian Graph Neural Networks with Adaptive Connection Sampling
Arman Hasanzadeh
Ehsan Hajiramezanali
Shahin Boluki
Mingyuan Zhou
N. Duffield
Krishna R. Narayanan
Xiaoning Qian
BDL
59
118
0
07 Jun 2020
Higher-Order Explanations of Graph Neural Networks via Relevant Walks
Higher-Order Explanations of Graph Neural Networks via Relevant Walks
Thomas Schnake
Oliver Eberle
Jonas Lederer
Shinichi Nakajima
Kristof T. Schütt
Klaus-Robert Muller
G. Montavon
106
223
0
05 Jun 2020
XGNN: Towards Model-Level Explanations of Graph Neural Networks
XGNN: Towards Model-Level Explanations of Graph Neural Networks
Haonan Yuan
Jiliang Tang
Helen Zhou
Shuiwang Ji
93
401
0
03 Jun 2020
Interpretable and Efficient Heterogeneous Graph Convolutional Network
Interpretable and Efficient Heterogeneous Graph Convolutional Network
Yaming Yang
Ziyu Guan
Jianxin Li
Wei Zhao
Jiangtao Cui
Quan Wang
GNN
100
176
0
27 May 2020
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional
  Networks
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks
Yimeng Min
Frederik Wenkel
Guy Wolf
GNN
141
114
0
18 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
337
1,128
0
13 Feb 2020
Capsules with Inverted Dot-Product Attention Routing
Capsules with Inverted Dot-Product Attention Routing
Yao-Hung Hubert Tsai
Nitish Srivastava
Hanlin Goh
Ruslan Salakhutdinov
74
81
0
12 Feb 2020
Independence Promoted Graph Disentangled Networks
Independence Promoted Graph Disentangled Networks
Yanbei Liu
Tianlin Li
Shu Wu
Zhitao Xiao
87
95
0
26 Nov 2019
A Capsule Network-based Model for Learning Node Embeddings
A Capsule Network-based Model for Learning Node Embeddings
Dai Quoc Nguyen
T. Nguyen
Dat Quoc Nguyen
Dinh Q. Phung
GNN
51
10
0
12 Nov 2019
Composition-based Multi-Relational Graph Convolutional Networks
Composition-based Multi-Relational Graph Convolutional Networks
Shikhar Vashishth
Soumya Sanyal
Vikram Nitin
Partha P. Talukdar
GNN
148
849
0
08 Nov 2019
Diffusion Improves Graph Learning
Diffusion Improves Graph Learning
Johannes Klicpera
Stefan Weißenberger
Stephan Günnemann
GNN
160
712
0
28 Oct 2019
Multi-scale Attributed Node Embedding
Multi-scale Attributed Node Embedding
Benedek Rozemberczki
Carl Allen
Rik Sarkar
GNN
273
866
0
28 Sep 2019
PairNorm: Tackling Oversmoothing in GNNs
PairNorm: Tackling Oversmoothing in GNNs
Lingxiao Zhao
Leman Akoglu
76
511
0
26 Sep 2019
Measuring and Relieving the Over-smoothing Problem for Graph Neural
  Networks from the Topological View
Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological View
Deli Chen
Yankai Lin
Wei Li
Peng Li
Jie Zhou
Xu Sun
97
1,113
0
07 Sep 2019
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
117
1,349
0
25 Jul 2019
Explainability Techniques for Graph Convolutional Networks
Explainability Techniques for Graph Convolutional Networks
Federico Baldassarre
Hossein Azizpour
GNNFAtt
178
272
0
31 May 2019
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified
  Neighborhood Mixing
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing
Sami Abu-El-Haija
Bryan Perozzi
Amol Kapoor
N. Alipourfard
Kristina Lerman
Hrayr Harutyunyan
Greg Ver Steeg
Aram Galstyan
GNN
105
918
0
30 Apr 2019
Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks
Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks
Matthias Fey
GNN
66
47
0
09 Apr 2019
DeepGCNs: Can GCNs Go as Deep as CNNs?
DeepGCNs: Can GCNs Go as Deep as CNNs?
Ge Li
Matthias Muller
Ali K. Thabet
Guohao Li
3DPCGNN
141
1,352
0
07 Apr 2019
GNNExplainer: Generating Explanations for Graph Neural Networks
GNNExplainer: Generating Explanations for Graph Neural Networks
Rex Ying
Dylan Bourgeois
Jiaxuan You
Marinka Zitnik
J. Leskovec
LLMAG
155
1,334
0
10 Mar 2019
Capsule Neural Networks for Graph Classification using Explicit
  Tensorial Graph Representations
Capsule Neural Networks for Graph Classification using Explicit Tensorial Graph Representations
Marcelo Daniel Gutierrez Mallea
Peter Meltzer
Peter J Bentley
GNN
43
21
0
22 Feb 2019
Simplifying Graph Convolutional Networks
Simplifying Graph Convolutional Networks
Felix Wu
Tianyi Zhang
Amauri Souza
Christopher Fifty
Tao Yu
Kilian Q. Weinberger
GNN
254
3,189
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
173
1,367
0
14 Nov 2018
Predict then Propagate: Graph Neural Networks meet Personalized PageRank
Predict then Propagate: Graph Neural Networks meet Personalized PageRank
Johannes Klicpera
Aleksandar Bojchevski
Stephan Günnemann
GNN
225
1,695
0
14 Oct 2018
Large-Scale Learnable Graph Convolutional Networks
Large-Scale Learnable Graph Convolutional Networks
Hongyang Gao
Zhengyang Wang
Shuiwang Ji
GNN
92
597
0
12 Aug 2018
Group Equivariant Capsule Networks
Group Equivariant Capsule Networks
J. E. Lenssen
Matthias Fey
Pascal Libuschewski
91
109
0
13 Jun 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
526
1,991
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
277
3,556
0
06 Jun 2018
Graph Capsule Convolutional Neural Networks
Graph Capsule Convolutional Neural Networks
Saurabh Verma
Zhi-Li Zhang
GNN
96
129
0
21 May 2018
Dynamic Graph CNN for Learning on Point Clouds
Dynamic Graph CNN for Learning on Point Clouds
Yue Wang
Yongbin Sun
Ziwei Liu
Sanjay E. Sarma
M. Bronstein
Justin Solomon
GNN3DPC
265
6,181
0
24 Jan 2018
Deeper Insights into Graph Convolutional Networks for Semi-Supervised
  Learning
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning
Qimai Li
Zhichao Han
Xiao-Ming Wu
GNNSSL
199
2,842
0
22 Jan 2018
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
491
20,296
0
30 Oct 2017
Dynamic Routing Between Capsules
Dynamic Routing Between Capsules
S. Sabour
Nicholas Frosst
Geoffrey E. Hinton
203
4,612
0
26 Oct 2017
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via
  Ranking
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking
Aleksandar Bojchevski
Stephan Günnemann
BDL
99
648
0
12 Jul 2017
struc2vec: Learning Node Representations from Structural Identity
struc2vec: Learning Node Representations from Structural Identity
Leonardo F. R. Ribeiro
Pedro H. P. Saverese
Daniel R. Figueiredo
106
1,164
0
11 Apr 2017
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on
  Graphs
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs
M. Simonovsky
N. Komodakis
GNN
234
1,232
0
10 Apr 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
600
7,501
0
04 Apr 2017
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
442
1,824
0
25 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNNSSL
700
29,220
0
09 Sep 2016
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