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Principal Neighbourhood Aggregation for Graph Nets

Principal Neighbourhood Aggregation for Graph Nets

12 April 2020
Gabriele Corso
Luca Cavalleri
Dominique Beaini
Pietro Lió
Petar Velickovic
    GNN
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Papers citing "Principal Neighbourhood Aggregation for Graph Nets"

19 / 119 papers shown
Title
Predicting cognitive scores with graph neural networks through sample
  selection learning
Predicting cognitive scores with graph neural networks through sample selection learning
M. Hanik
Mehmet Arif Demirtas
Mohammed Amine Gharsallaoui
I. Rekik
16
13
0
17 Jun 2021
First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph
  Prediction Track
First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track
Chengxuan Ying
Mingqi Yang
Shuxin Zheng
Guolin Ke
Shengjie Luo
Tianle Cai
Chenglin Wu
Yuxin Wang
Yanming Shen
Di He
16
11
0
15 Jun 2021
Neural Bellman-Ford Networks: A General Graph Neural Network Framework
  for Link Prediction
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
Zhaocheng Zhu
Zuobai Zhang
Louis-Pascal Xhonneux
Jian Tang
GNN
27
300
0
13 Jun 2021
Do Transformers Really Perform Bad for Graph Representation?
Do Transformers Really Perform Bad for Graph Representation?
Chengxuan Ying
Tianle Cai
Shengjie Luo
Shuxin Zheng
Guolin Ke
Di He
Yanming Shen
Tie-Yan Liu
GNN
28
433
0
09 Jun 2021
Rethinking Graph Transformers with Spectral Attention
Rethinking Graph Transformers with Spectral Attention
Devin Kreuzer
Dominique Beaini
William L. Hamilton
Vincent Létourneau
Prudencio Tossou
43
505
0
07 Jun 2021
Do We Need Anisotropic Graph Neural Networks?
Do We Need Anisotropic Graph Neural Networks?
Shyam A. Tailor
Felix L. Opolka
Pietro Lio'
Nicholas D. Lane
40
34
0
03 Apr 2021
Size-Invariant Graph Representations for Graph Classification
  Extrapolations
Size-Invariant Graph Representations for Graph Classification Extrapolations
Beatrice Bevilacqua
Yangze Zhou
Bruno Ribeiro
OOD
35
108
0
08 Mar 2021
Weisfeiler and Lehman Go Topological: Message Passing Simplicial
  Networks
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
Cristian Bodnar
Fabrizio Frasca
Yu Guang Wang
N. Otter
Guido Montúfar
Pietro Lió
M. Bronstein
31
247
0
04 Mar 2021
Combinatorial optimization and reasoning with graph neural networks
Combinatorial optimization and reasoning with graph neural networks
Quentin Cappart
Didier Chételat
Elias Boutros Khalil
Andrea Lodi
Christopher Morris
Petar Velickovic
AI4CE
32
347
0
18 Feb 2021
Learning Aggregation Functions
Learning Aggregation Functions
Giovanni Pellegrini
Alessandro Tibo
P. Frasconi
Andrea Passerini
M. Jaeger
FedML
10
19
0
15 Dec 2020
Universal Activation Function For Machine Learning
Universal Activation Function For Machine Learning
Brosnan Yuen
Minh Tu Hoang
Xiaodai Dong
Tao Lu
18
40
0
07 Nov 2020
From Local Structures to Size Generalization in Graph Neural Networks
From Local Structures to Size Generalization in Graph Neural Networks
Gilad Yehudai
Ethan Fetaya
E. Meirom
Gal Chechik
Haggai Maron
GNN
AI4CE
169
123
0
17 Oct 2020
A Unified View on Graph Neural Networks as Graph Signal Denoising
A Unified View on Graph Neural Networks as Graph Signal Denoising
Yao Ma
Xiaorui Liu
Tong Zhao
Yozen Liu
Jiliang Tang
Neil Shah
AI4CE
36
176
0
05 Oct 2020
Hierarchical Protein Function Prediction with Tail-GNNs
Hierarchical Protein Function Prediction with Tail-GNNs
Stefan Spalević
Petar Velivcković
Jovana Kovavcević
Mladen Nikolic
AI4CE
15
5
0
24 Jul 2020
Improving Graph Neural Network Expressivity via Subgraph Isomorphism
  Counting
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting
Giorgos Bouritsas
Fabrizio Frasca
S. Zafeiriou
M. Bronstein
46
424
0
16 Jun 2020
A Survey on The Expressive Power of Graph Neural Networks
A Survey on The Expressive Power of Graph Neural Networks
Ryoma Sato
184
172
0
09 Mar 2020
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
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
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
253
3,239
0
24 Nov 2016
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