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
Repetition Makes Perfect: Recurrent Sum-GNNs Match Message Passing Limit Eran Rosenbluth Martin Grohe 19 0 0 01 May 2025
Towards Invariance to Node Identifiers in Graph Neural Networks Maya Bechler-Speicher Moshe Eliasof Carola-Bibiane Schönlieb Ran Gilad-Bachrach Amir Globerson 56 1 0 20 Feb 2025
Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings Billy Joe Franks Moshe Eliasof Semih Cantürk Guy Wolf Carola-Bibiane Schönlieb Sophie Fellenz Marius Kloft AI4CE 76 0 0 10 Dec 2024
Joint Estimation and Prediction of City-wide Delivery Demand: A Large Language Model Empowered Graph-based Learning Approach Tong Nie Junlin He Yuewen Mei Guoyang Qin Guilong Li Jian Sun Wei Ma 32 3 0 30 Aug 2024
Scalable Graph Compressed Convolutions Junshu Sun Chen Yang Shuhui Wang Qingming Huang GNN 43 0 0 26 Jul 2024
Revisiting Random Walks for Learning on Graphs Jinwoo Kim Olga Zaghen Ayhan Suleymanzade Youngmin Ryou Seunghoon Hong 59 0 0 01 Jul 2024
Learning Domain-Independent Heuristics for Grounded and Lifted Planning Dillon Z. Chen Sylvie Thiébaux Felipe W. Trevizan AI4CE 29 15 0 18 Dec 2023
Random Entity Quantization for Parameter-Efficient Compositional Knowledge Graph Representation Jiaang Li Quan Wang Yi Liu L. Zhang Zhendong Mao 27 0 0 24 Oct 2023
Graph-level Representation Learning with Joint-Embedding Predictive Architectures Geri Skenderi Hang Li Jiliang Tang Marco Cristani AI4TS GNN 54 3 0 27 Sep 2023
How Expressive are Graph Neural Networks in Recommendation? Xuheng Cai Lianghao Xia Xubin Ren Chao Huang 29 6 0 22 Aug 2023
The Expressive Power of Graph Neural Networks: A Survey Bingxue Zhang Changjun Fan Shixuan Liu Kuihua Huang Xiang Zhao Jin-Yu Huang Zhong Liu 40 19 0 16 Aug 2023
Expectation-Complete Graph Representations with Homomorphisms Pascal Welke Maximilian Thiessen Fabian Jogl Thomas Gärtner 18 6 0 09 Jun 2023
Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman Jiarui Feng Lecheng Kong Hao Liu Dacheng Tao Fuhai Li Muhan Zhang Yixin Chen 44 10 0 05 Jun 2023
From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks Cai Zhou Xiyuan Wang Muhan Zhang 28 14 0 08 May 2023
An Empirical Study of Realized GNN Expressiveness Yanbo Wang Muhan Zhang 39 10 0 16 Apr 2023
Graph Positional Encoding via Random Feature Propagation Moshe Eliasof Fabrizio Frasca Beatrice Bevilacqua Eran Treister Gal Chechik Haggai Maron 22 18 0 06 Mar 2023
Technical report: Graph Neural Networks go Grammatical Jason Piquenot Aldo Moscatelli Maxime Bérar Pierre Héroux R. Raveaux Jean-Yves Ramel Sébastien Adam 25 1 0 02 Mar 2023
Equivariant Polynomials for Graph Neural Networks Omri Puny Derek Lim B. Kiani Haggai Maron Y. Lipman 24 31 0 22 Feb 2023
A Theory of Link Prediction via Relational Weisfeiler-Leman on Knowledge Graphs Xingyue Huang Miguel Romero .Ismail .Ilkan Ceylan Pablo Barceló 32 24 0 04 Feb 2023
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure Ryoma Sato 31 5 0 26 Jan 2023
A Generalization of ViT/MLP-Mixer to Graphs Xiaoxin He Bryan Hooi T. Laurent Adam Perold Yann LeCun Xavier Bresson 36 88 0 27 Dec 2022
Beyond 1-WL with Local Ego-Network Encodings Nurudin Alvarez-Gonzalez Andreas Kaltenbrunner Vicencc Gómez 33 5 0 27 Nov 2022
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks Anders Aamand Justin Y. Chen Piotr Indyk Shyam Narayanan R. Rubinfeld Nicholas Schiefer Sandeep Silwal Tal Wagner 39 21 0 06 Nov 2022
Boosting the Cycle Counting Power of Graph Neural Networks with I $^2$ -GNNs Yinan Huang Xingang Peng Jianzhu Ma Muhan Zhang 81 47 0 22 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
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 18 22 0 22 Aug 2022
Universally Expressive Communication in Multi-Agent Reinforcement Learning Matthew Morris Thomas D. Barrett Arnu Pretorius 24 4 0 14 Jun 2022
Shortest Path Networks for Graph Property Prediction Ralph Abboud Radoslav Dimitrov .Ismail .Ilkan Ceylan GNN 27 44 0 02 Jun 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 44 39 0 25 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 35 65 0 09 Mar 2022
R-GCN: The R Could Stand for Random Vic Degraeve Gilles Vandewiele F. Ongenae Sofie Van Hoecke GNN 21 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
A Theoretical Comparison of Graph Neural Network Extensions Pál András Papp Roger Wattenhofer 97 45 0 30 Jan 2022
Equivariant Quantum Graph Circuits Péter Mernyei K. Meichanetzidis .Ismail .Ilkan Ceylan 36 8 0 10 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 23 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 19 138 0 11 Nov 2021
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness Lingxiao Zhao Wei Jin L. 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 48 174 0 06 Oct 2021
Reconstruction for Powerful Graph Representations Leonardo Cotta Christopher Morris Bruno Ribeiro AI4CE 127 78 0 01 Oct 2021
Learning General Optimal Policies with Graph Neural Networks: Expressive Power, Transparency, and Limits Simon Ståhlberg Blai Bonet Hector Geffner 27 48 0 21 Sep 2021
Graph Neural Networks for Graph Drawing Matteo Tiezzi Gabriele Ciravegna Marco Gori 21 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
Graph Neural Networks with Local Graph Parameters Pablo Barceló Floris Geerts Juan L. Reutter Maksimilian Ryschkov 24 64 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 13 121 0 08 Jun 2021
The Logic of Graph Neural Networks Martin Grohe AI4CE 18 87 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 32 346 0 18 Feb 2021
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 189 914 0 02 Mar 2020
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 203 885 0 07 Jun 2018