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GPNet: Simplifying Graph Neural Networks via Multi-channel Geometric
  Polynomials

GPNet: Simplifying Graph Neural Networks via Multi-channel Geometric Polynomials

30 September 2022
Xun Liu
Alex Hay-Man Ng
Fangyu Lei
Yikuan Zhang
Zhengmin Li
    GNN
ArXivPDFHTML

Papers citing "GPNet: Simplifying Graph Neural Networks via Multi-channel Geometric Polynomials"

4 / 4 papers shown
Title
Beyond Low-frequency Information in Graph Convolutional Networks
Beyond Low-frequency Information in Graph Convolutional Networks
Deyu Bo
Xiao Wang
C. Shi
Huawei Shen
GNN
87
554
0
04 Jan 2021
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
169
1,072
0
13 Feb 2020
Multi-scale Attributed Node Embedding
Multi-scale Attributed Node Embedding
Benedek Rozemberczki
Carl Allen
Rik Sarkar
GNN
145
833
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
229
1,935
0
09 Jun 2018
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