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Effects of Graph Convolutions in Multi-layer Networks

Effects of Graph Convolutions in Multi-layer Networks

20 April 2022
Aseem Baranwal
Kimon Fountoulakis
Aukosh Jagannath
ArXivPDFHTML

Papers citing "Effects of Graph Convolutions in Multi-layer Networks"

16 / 16 papers shown
Title
Optimality of Message-Passing Architectures for Sparse Graphs
Optimality of Message-Passing Architectures for Sparse Graphs
Aseem Baranwal
Kimon Fountoulakis
Aukosh Jagannath
155
11
0
10 Jan 2025
Exact Community Recovery in Correlated Stochastic Block Models
Exact Community Recovery in Correlated Stochastic Block Models
Julia Gaudio
Miklós Z. Rácz
Anirudh Sridhar
48
10
0
29 Mar 2022
Is Homophily a Necessity for Graph Neural Networks?
Is Homophily a Necessity for Graph Neural Networks?
Yao Ma
Xiaorui Liu
Neil Shah
Jiliang Tang
54
233
0
11 Jun 2021
Graph Convolution for Semi-Supervised Classification: Improved Linear
  Separability and Out-of-Distribution Generalization
Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization
Aseem Baranwal
Kimon Fountoulakis
Aukosh Jagannath
OODD
100
76
0
13 Feb 2021
Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph
  Convolutional Neural Networks
Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks
Yujun Yan
Milad Hashemi
Kevin Swersky
Yaoqing Yang
Danai Koutra
92
252
0
12 Feb 2021
How Neural Networks Extrapolate: From Feedforward to Graph Neural
  Networks
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Keyulu Xu
Mozhi Zhang
Jingling Li
S. Du
Ken-ichi Kawarabayashi
Stefanie Jegelka
MLT
101
312
0
24 Sep 2020
Adaptive Universal Generalized PageRank Graph Neural Network
Adaptive Universal Generalized PageRank Graph Neural Network
Eli Chien
Jianhao Peng
Pan Li
O. Milenkovic
240
736
0
14 Jun 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Weihua Hu
Matthias Fey
Marinka Zitnik
Yuxiao Dong
Hongyu Ren
Bowen Liu
Michele Catasta
J. Leskovec
285
2,725
0
02 May 2020
Fast Graph Representation Learning with PyTorch Geometric
Fast Graph Representation Learning with PyTorch Geometric
Matthias Fey
J. E. Lenssen
3DH
GNN
3DPC
208
4,334
0
06 Mar 2019
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
210
1,683
0
14 Oct 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
GNN
BDL
244
3,524
0
06 Jun 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
GNN
SSL
180
2,820
0
22 Jan 2018
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
522
7,431
0
04 Apr 2017
Interaction Networks for Learning about Objects, Relations and Physics
Interaction Networks for Learning about Objects, Relations and Physics
Peter W. Battaglia
Razvan Pascanu
Matthew Lai
Danilo Jimenez Rezende
Koray Kavukcuoglu
AI4CE
OCL
PINN
GNN
514
1,407
0
01 Dec 2016
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
400
1,819
0
25 Nov 2016
Supervised Random Walks: Predicting and Recommending Links in Social
  Networks
Supervised Random Walks: Predicting and Recommending Links in Social Networks
L. Backstrom
J. Leskovec
88
1,130
0
17 Nov 2010
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