The Surprising Power of Graph Neural Networks with Random Node Initialization

2 October 2020

Ralph Abboud

.Ismail .Ilkan Ceylan

Martin Grohe

Thomas Lukasiewicz

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Papers citing "The Surprising Power of Graph Neural Networks with Random Node Initialization"

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Title
Uplifting Message Passing Neural Network with Graph Original Information Xiao Liu Lijun Zhang Hui Guan GNN 26 2 0 08 Oct 2022
Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs Silvia Beddar-Wiesing Giuseppe Alessio D’Inverno C. Graziani Veronica Lachi Alice Moallemy-Oureh F. Scarselli J. M. Thomas 31 9 0 08 Oct 2022
Graph Neural Networks for Link Prediction with Subgraph Sketching B. Chamberlain S. Shirobokov Emanuele Rossi Fabrizio Frasca Thomas Markovich Nils Y. Hammerla Michael M. Bronstein Max Hansmire 54 78 0 30 Sep 2022
Provably expressive temporal graph networks Amauri Souza Diego Mesquita Samuel Kaski Vikas K. Garg 89 54 0 29 Sep 2022
One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction Jan Tonshoff Berke Kisin Jakob Lindner Martin Grohe GNN 24 22 0 22 Aug 2022
A Topological characterisation of Weisfeiler-Leman equivalence classes Jacob Bamberger GNN 24 3 0 23 Jun 2022
Ordered Subgraph Aggregation Networks Chao Qian Gaurav Rattan Floris Geerts Christopher Morris Mathias Niepert 46 57 0 22 Jun 2022
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries Fabrizio Frasca Beatrice Bevilacqua Michael M. Bronstein Haggai Maron 43 125 0 22 Jun 2022
Agent-based Graph Neural Networks Karolis Martinkus Pál András Papp Benedikt Schesch Roger Wattenhofer LLMAG GNN 37 17 0 22 Jun 2022
Taxonomy of Benchmarks in Graph Representation Learning Renming Liu Semih Cantürk Frederik Wenkel Sarah McGuire Devin Kreuzer ... Michael Perlmutter Bastian Alexander Rieck M. Hirn Guy Wolf Ladislav Rampášek OOD 26 14 0 15 Jun 2022
Universally Expressive Communication in Multi-Agent Reinforcement Learning Matthew Morris Thomas D. Barrett Arnu Pretorius 24 4 0 14 Jun 2022
Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm Meng Liu Haiyang Yu Shuiwang Ji 38 1 0 04 Jun 2022
Shortest Path Networks for Graph Property Prediction Ralph Abboud Radoslav Dimitrov .Ismail .Ilkan Ceylan GNN 27 45 0 02 Jun 2022
Graph Neural Networks with Precomputed Node Features Béni Egressy Roger Wattenhofer 17 2 0 01 Jun 2022
Going Deeper into Permutation-Sensitive Graph Neural Networks Zhongyu Huang Yingheng Wang Chaozhuo Li Huiguang He 19 31 0 28 May 2022
How Powerful are K-hop Message Passing Graph Neural Networks Jiarui Feng Yixin Chen Fuhai Li Anindya Sarkar Muhan Zhang 14 100 0 26 May 2022
How Powerful are Spectral Graph Neural Networks Xiyuan Wang Muhan Zhang 80 181 0 23 May 2022
Representation Power of Graph Neural Networks: Improved Expressivity via Algebraic Analysis Charilaos I. Kanatsoulis Alejandro Ribeiro 36 4 0 19 May 2022
Learning Generalized Policies Without Supervision Using GNNs Simon Ståhlberg Blai Bonet Hector Geffner OffRL 26 27 0 12 May 2022
Theory of Graph Neural Networks: Representation and Learning Stefanie Jegelka GNN AI4CE 33 68 0 16 Apr 2022
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks Christopher Morris Gaurav Rattan Sandra Kiefer Siamak Ravanbakhsh 50 40 0 25 Mar 2022
Twin Weisfeiler-Lehman: High Expressive GNNs for Graph Classification Zhaohui Wang Qi Cao Huawei Shen Bingbing Xu Xueqi Cheng 28 2 0 22 Mar 2022
On the expressive power of message-passing neural networks as global feature map transformers Floris Geerts Jasper Steegmans Jan Van den Bussche 17 6 0 17 Mar 2022
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets Yu Shi Shuxin Zheng Guolin Ke Yifei Shen Jiacheng You Jiyan He Shengjie Luo Chang-Shu Liu Di He Tie-Yan Liu AI4CE 45 65 0 09 Mar 2022
R-GCN: The R Could Stand for Random Vic Degraeve Gilles Vandewiele F. Ongenae Sofie Van Hoecke GNN 29 13 0 04 Mar 2022
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks Hongya Wang Haoteng Yin Muhan Zhang Pan Li 35 107 0 01 Mar 2022
An Empirical Study of Graphormer on Large-Scale Molecular Modeling Datasets Yu Shi Shuxin Zheng Guolin Ke Yifei Shen Jiacheng You Jiyan He Shengjie Luo Chang-Shu Liu Di He Tie-Yan Liu AI4CE 24 0 0 28 Feb 2022
1-WL Expressiveness Is (Almost) All You Need Markus Zopf 19 11 0 21 Feb 2022
Weisfeiler and Leman Go Infinite: Spectral and Combinatorial Pre-Colorings Or Feldman A. Boyarski Shai Feldman D. Kogan A. Mendelson Chaim Baskin 40 14 0 31 Jan 2022
A Theoretical Comparison of Graph Neural Network Extensions Pál András Papp Roger Wattenhofer 103 46 0 30 Jan 2022
Weisfeiler and Leman go Machine Learning: The Story so far Christopher Morris Y. Lipman Haggai Maron Bastian Alexander Rieck Nils M. Kriege Martin Grohe Matthias Fey Karsten M. Borgwardt GNN 43 112 0 18 Dec 2021
Equivariant Quantum Graph Circuits Péter Mernyei K. Meichanetzidis .Ismail .Ilkan Ceylan 42 8 0 10 Dec 2021
A systematic approach to random data augmentation on graph neural networks Billy Joe Franks Markus Anders Marius Kloft Pascal Schweitzer OOD AAML 11 0 0 08 Dec 2021
On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features Emanuele Rossi Henry Kenlay Maria I. Gorinova B. Chamberlain Xiaowen Dong M. Bronstein 34 87 0 23 Nov 2021
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks Pál András Papp Karolis Martinkus Lukas Faber Roger Wattenhofer GNN 28 138 0 11 Nov 2021
Nested Graph Neural Networks Muhan Zhang Pan Li 27 163 0 25 Oct 2021
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness Lingxiao Zhao Wei Jin Leman Akoglu Neil Shah GNN 24 160 0 07 Oct 2021
Equivariant Subgraph Aggregation Networks Beatrice Bevilacqua Fabrizio Frasca Derek Lim Balasubramaniam Srinivasan Chen Cai G. Balamurugan M. Bronstein Haggai Maron 53 176 0 06 Oct 2021
Reconstruction for Powerful Graph Representations Leonardo Cotta Christopher Morris Bruno Ribeiro AI4CE 130 78 0 01 Oct 2021
Learning General Optimal Policies with Graph Neural Networks: Expressive Power, Transparency, and Limits Simon Ståhlberg Blai Bonet Hector Geffner 41 48 0 21 Sep 2021
Graph Neural Networks for Graph Drawing Matteo Tiezzi Gabriele Ciravegna Marco Gori 26 20 0 21 Sep 2021
On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs Hejie Cui Zijie Lu Pan Li Carl Yang 15 80 0 03 Jul 2021
On the approximation capability of GNNs in node classification/regression tasks Giuseppe Alessio D’Inverno Monica Bianchini M. Sampoli F. Scarselli 34 12 0 16 Jun 2021
Graph Neural Networks with Local Graph Parameters Pablo Barceló Floris Geerts Juan L. Reutter Maksimilian Ryschkov 24 65 0 12 Jun 2021
Breaking the Limits of Message Passing Graph Neural Networks M. Balcilar Pierre Héroux Benoit Gaüzère Pascal Vasseur Sébastien Adam P. Honeine 21 121 0 08 Jun 2021
On the Universality of Graph Neural Networks on Large Random Graphs Nicolas Keriven A. Bietti Samuel Vaiter 36 23 0 27 May 2021
The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs Christopher Morris Matthias Fey Nils M. Kriege GNN 31 23 0 12 May 2021
The Logic of Graph Neural Networks Martin Grohe AI4CE 23 88 0 29 Apr 2021
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
Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing Jan Toenshoff Martin Ritzert Hinrikus Wolf Martin Grohe GNN 84 28 0 17 Feb 2021