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Node2Seq: Towards Trainable Convolutions in Graph Neural Networks

Node2Seq: Towards Trainable Convolutions in Graph Neural Networks

6 January 2021
Hao Yuan
Shuiwang Ji
    GNN
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Papers citing "Node2Seq: Towards Trainable Convolutions in Graph Neural Networks"

5 / 5 papers shown
Title
Explainability in Graph Neural Networks: A Taxonomic Survey
Explainability in Graph Neural Networks: A Taxonomic Survey
Hao Yuan
Haiyang Yu
Shurui Gui
Shuiwang Ji
156
463
0
31 Dec 2020
Line Graph Neural Networks for Link Prediction
Line Graph Neural Networks for Link Prediction
Lei Cai
Jundong Li
Jie Wang
Shuiwang Ji
GNN
127
194
0
20 Oct 2020
Multi-scale Attributed Node Embedding
Multi-scale Attributed Node Embedding
Benedek Rozemberczki
Carl Allen
Rik Sarkar
GNN
139
828
0
28 Sep 2019
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
217
1,726
0
09 Jun 2018
Convolutional Neural Networks for Sentence Classification
Convolutional Neural Networks for Sentence Classification
Yoon Kim
AILaw
VLM
238
13,283
0
25 Aug 2014
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