Graph Neural Networks with Local Graph Parameters

12 June 2021

Papers citing "Graph Neural Networks with Local Graph Parameters"

38 / 38 papers shown

Title
Counting Substructures with Higher-Order Graph Neural Networks: Possibility and Impossibility Results B. Tahmasebi Derek Lim Stefanie Jegelka GNN 102 30 0 06 Dec 2020
The Surprising Power of Graph Neural Networks with Random Node Initialization Ralph Abboud .Ismail .Ilkan Ceylan Martin Grohe Thomas Lukasiewicz 82 221 0 02 Oct 2020
The expressive power of kth-order invariant graph networks Floris Geerts 142 37 0 23 Jul 2020
A Novel Higher-order Weisfeiler-Lehman Graph Convolution C. Damke Vitali M. Melnikov Eyke Hüllermeier GNN 35 14 0 01 Jul 2020
Expressive Power of Invariant and Equivariant Graph Neural Networks Waïss Azizian Marc Lelarge 62 111 0 28 Jun 2020
Building powerful and equivariant graph neural networks with structural message-passing Clément Vignac Andreas Loukas P. Frossard 50 121 0 26 Jun 2020
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Giorgos Bouritsas Fabrizio Frasca Stefanos Zafeiriou M. Bronstein 109 430 0 16 Jun 2020
Weisfeiler-Lehman Embedding for Molecular Graph Neural Networks Katsuhiko Ishiguro Kenta Oono K. Hayashi GNN 40 4 0 12 Jun 2020
Machine Learning on Graphs: A Model and Comprehensive Taxonomy Ines Chami Sami Abu-El-Haija Bryan Perozzi Christopher Ré Kevin Patrick Murphy 85 289 0 07 May 2020
Graph Homomorphism Convolution Hoang NT Takanori Maehara 124 41 0 03 May 2020
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
Let's Agree to Degree: Comparing Graph Convolutional Networks in the Message-Passing Framework Floris Geerts Filip Mazowiecki Guillermo A. Pérez GNN 58 38 0 06 Apr 2020
word2vec, node2vec, graph2vec, X2vec: Towards a Theory of Vector Embeddings of Structured Data Martin Grohe 70 172 0 27 Mar 2020
A Survey on The Expressive Power of Graph Neural Networks Ryoma Sato 306 172 0 09 Mar 2020
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 387 939 0 02 Mar 2020
Generalization and Representational Limits of Graph Neural Networks Vikas Garg Stefanie Jegelka Tommi Jaakkola GNN 94 312 0 14 Feb 2020
Can Graph Neural Networks Count Substructures? Zhengdao Chen Lei Chen Soledad Villar Joan Bruna GNN 109 324 0 10 Feb 2020
Random Features Strengthen Graph Neural Networks Ryoma Sato M. Yamada H. Kashima GNN AAML 68 237 0 08 Feb 2020
A Hierarchy of Graph Neural Networks Based on Learnable Local Features M. Li Meng Dong Jiawei Zhou Alexander M. Rush AI4CE GNN 55 7 0 13 Nov 2019
Quantifying the Carbon Emissions of Machine Learning Alexandre Lacoste A. Luccioni Victor Schmidt Thomas Dandres 86 695 0 21 Oct 2019
What graph neural networks cannot learn: depth vs width Andreas Loukas GNN 82 299 0 06 Jul 2019
On the equivalence between graph isomorphism testing and function approximation with GNNs Zhengdao Chen Soledad Villar Lei Chen Joan Bruna 78 281 0 29 May 2019
Provably Powerful Graph Networks Haggai Maron Heli Ben-Hamu Hadar Serviansky Y. Lipman 108 578 0 27 May 2019
Approximation Ratios of Graph Neural Networks for Combinatorial Problems Ryoma Sato M. Yamada H. Kashima GNN 85 128 0 24 May 2019
Universal Invariant and Equivariant Graph Neural Networks Nicolas Keriven Gabriel Peyré 160 292 0 13 May 2019
Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification Ting-Li Chen Song Bian Yizhou Sun 85 88 0 11 May 2019
On the Universality of Invariant Networks Haggai Maron Ethan Fetaya Nimrod Segol Y. Lipman OOD 145 238 0 27 Jan 2019
A Comprehensive Survey on Graph Neural Networks Zonghan Wu Shirui Pan Fengwen Chen Guodong Long Chengqi Zhang Philip S. Yu FaML GNN AI4TS AI4CE 664 8,496 0 03 Jan 2019
Invariant and Equivariant Graph Networks Haggai Maron Heli Ben-Hamu Nadav Shamir Y. Lipman 113 502 0 24 Dec 2018
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks Christopher Morris Martin Ritzert Matthias Fey William L. Hamilton J. E. Lenssen Gaurav Rattan Martin Grohe GNN 179 1,630 0 04 Oct 2018
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 222 7,623 0 01 Oct 2018
Residual Gated Graph ConvNets Xavier Bresson T. Laurent GNN 118 481 0 20 Nov 2017
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 434 20,089 0 30 Oct 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 460 15,179 0 07 Jun 2017
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
Community Detection and Stochastic Block Models Emmanuel Abbe 126 1,192 0 29 Mar 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 402 1,819 0 25 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 585 28,999 0 09 Sep 2016