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A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs

6 November 2022

Papers citing "A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs"

28 / 28 papers shown

Title
Graph Sampling for Scalable and Expressive Graph Neural Networks on Homophilic Graphs Haolin Li Luana Ruiz Luana Ruiz 92 0 0 22 Oct 2024
Fine-grained Expressivity of Graph Neural Networks Jan Böker Ron Levie Ningyuan Huang Soledad Villar Christopher Morris 98 21 0 06 Jun 2023
Satellite Navigation and Coordination with Limited Information Sharing Sydney I. Dolan Siddharth Nayak H. Balakrishnan 62 5 0 07 Nov 2022
How Powerful are Spectral Graph Neural Networks Xiyuan Wang Muhan Zhang 126 201 0 23 May 2022
Effects of Graph Convolutions in Multi-layer Networks Aseem Baranwal Kimon Fountoulakis Aukosh Jagannath 85 26 0 20 Apr 2022
When Does A Spectral Graph Neural Network Fail in Node Classification? Zhi-Xing Chen Tengfei Ma Yangkun Wang 92 13 0 16 Feb 2022
Transferability Properties of Graph Neural Networks Luana Ruiz Luiz F. O. Chamon Alejandro Ribeiro GNN 74 42 0 09 Dec 2021
Is Homophily a Necessity for Graph Neural Networks? Yao Ma Xiaorui Liu Neil Shah Jiliang Tang 54 236 0 11 Jun 2021
Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization Aseem Baranwal Kimon Fountoulakis Aukosh Jagannath OODD 140 76 0 13 Feb 2021
Combining Label Propagation and Simple Models Out-performs Graph Neural Networks Qian Huang Horace He Abhay Singh Ser-Nam Lim Austin R. Benson 91 283 0 27 Oct 2020
Graph Neural Networks: Architectures, Stability and Transferability Luana Ruiz Fernando Gama Alejandro Ribeiro GNN 126 129 0 04 Aug 2020
On spectral algorithms for community detection in stochastic blockmodel graphs with vertex covariates Cong Mu A. Mele Lingxin Hao Joshua Cape A. Athreya Carey E. Priebe 41 11 0 04 Jul 2020
Graphon Neural Networks and the Transferability of Graph Neural Networks Luana Ruiz Luiz F. O. Chamon Alejandro Ribeiro GNN 85 148 0 05 Jun 2020
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 334 1,124 0 13 Feb 2020
Multi-scale Attributed Node Embedding Benedek Rozemberczki Carl Allen Rik Sarkar GNN 271 864 0 28 Sep 2019
Spectral inference for large Stochastic Blockmodels with nodal covariates A. Mele Lingxin Hao Joshua Cape Carey E. Priebe 133 20 0 18 Aug 2019
Inference for multiple heterogeneous networks with a common invariant subspace Jesús Arroyo A. Athreya Joshua Cape Guodong Chen Carey E. Priebe Joshua T. Vogelstein 67 117 0 24 Jun 2019
Universal Invariant and Equivariant Graph Neural Networks Nicolas Keriven Gabriel Peyré 196 294 0 13 May 2019
Stability Properties of Graph Neural Networks Fernando Gama Joan Bruna Alejandro Ribeiro 93 235 0 11 May 2019
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 247 4,368 0 06 Mar 2019
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 259 7,705 0 01 Oct 2018
On spectral embedding performance and elucidating network structure in stochastic block model graphs Joshua Cape M. Tang Carey E. Priebe 48 23 0 14 Aug 2018
Statistical inference on random dot product graphs: a survey A. Athreya D. E. Fishkind Keith D. Levin V. Lyzinski Youngser Park Yichen Qin D. Sussman M. Tang Joshua T. Vogelstein Carey E. Priebe 146 249 0 16 Sep 2017
Weighted Message Passing and Minimum Energy Flow for Heterogeneous Stochastic Block Models with Side Information T. Tony Cai Tengyuan Liang Alexander Rakhlin 66 9 0 12 Sep 2017
Community Detection and Stochastic Block Models Emmanuel Abbe 138 1,200 0 29 Mar 2017
Covariate-assisted spectral clustering Norbert Binkiewicz Joshua T. Vogelstein Karl Rohe 91 153 0 08 Nov 2014
Regularized Spectral Clustering under the Degree-Corrected Stochastic Blockmodel Tai Qin Karl Rohe 133 303 0 16 Sep 2013
Stochastic blockmodels with growing number of classes David S. Choi P. Wolfe E. Airoldi 243 259 0 21 Nov 2010