The Surprising Power of Graph Neural Networks with Random Node Initialization

2 October 2020

Ralph Abboud

.Ismail .Ilkan Ceylan

Martin Grohe

Thomas Lukasiewicz

ArXiv PDF HTML

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

50 / 154 papers shown

Title
Data-centric Graph Learning: A Survey Jixi Liu Deyu Bo Cheng Yang Haoran Dai Qi Zhang Yixin Xiao Yufei Peng Chuan Shi GNN 30 19 0 08 Oct 2023
On the Two Sides of Redundancy in Graph Neural Networks Vidya Sagar Sharma Samir Moustafa Johannes Langguth Wilfried N. Gansterer Nils M. Kriege 32 1 0 06 Oct 2023
Probabilistically Rewired Message-Passing Neural Networks Chendi Qian Andrei Manolache Kareem Ahmed Zhe Zeng Mathias Niepert Mathias Niepert Christopher Morris 39 12 0 03 Oct 2023
Cooperative Graph Neural Networks Ben Finkelshtein Xingyue Huang Michael M. Bronstein .Ismail .Ilkan Ceylan GNN 40 20 0 02 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
Recovering Missing Node Features with Local Structure-based Embeddings Victor M. Tenorio Madeline Navarro Santiago Segarra Antonio G. Marques 17 2 0 16 Sep 2023
Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power Junru Zhou Jiarui Feng Xiyuan Wang Muhan Zhang 27 8 0 10 Sep 2023
Pure Message Passing Can Estimate Common Neighbor for Link Prediction Kaiwen Dong Zhichun Guo Nitesh V. Chawla 27 7 0 02 Sep 2023
Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability Zehao Dong Muhan Zhang Philip R. O. Payne Michael Province C. Cruchaga Tianyu Zhao Fuhai Li Yixin Chen 40 1 0 01 Sep 2023
How Expressive are Graph Neural Networks in Recommendation? Xuheng Cai Lianghao Xia Xubin Ren Chao Huang 38 6 0 22 Aug 2023
Geometric instability of graph neural networks on large graphs Emily L Morris Haotian Shen Weiling Du Muhammad Hamza Sajjad Borun Shi GNN 33 0 0 19 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
Tango: rethinking quantization for graph neural network training on GPUs Shiyang Chen Da Zheng Caiwen Ding Chengying Huan Yuede Ji Hang Liu GNN MQ 31 5 0 02 Aug 2023
Graph Positional and Structural Encoder Semih Cantürk Renming Liu Olivier Lapointe-Gagné Vincent Létourneau Guy Wolf Dominique Beaini Ladislav Rampášek 41 15 0 14 Jul 2023
GRAN is superior to GraphRNN: node orderings, kernel- and graph embeddings-based metrics for graph generators Ousmane Touat Julian Stier Pierre-Edouard Portier Michael Granitzer 14 1 0 13 Jul 2023
PlanE: Representation Learning over Planar Graphs Radoslav Dimitrov Zeyang Zhao Ralph Abboud .Ismail .Ilkan Ceylan GNN 32 10 0 03 Jul 2023
Provably Powerful Graph Neural Networks for Directed Multigraphs Béni Egressy Luc von Niederhäusern Jovan Blanusa Erik Altman Roger Wattenhofer Kubilay Atasu 27 15 0 20 Jun 2023
Path Neural Networks: Expressive and Accurate Graph Neural Networks Gaspard Michel Giannis Nikolentzos J. Lutzeyer Michalis Vazirgiannis GNN 18 26 0 09 Jun 2023
Expectation-Complete Graph Representations with Homomorphisms Pascal Welke Maximilian Thiessen Fabian Jogl Thomas Gärtner 18 6 0 09 Jun 2023
Limits, approximation and size transferability for GNNs on sparse graphs via graphops Thien Le Stefanie Jegelka 35 10 0 07 Jun 2023
Fine-grained Expressivity of Graph Neural Networks Jan Böker Ron Levie Ningyuan Huang Soledad Villar Christopher Morris 28 20 0 06 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 46 10 0 05 Jun 2023
Classification of Edge-dependent Labels of Nodes in Hypergraphs Minyoung Choe Sunwoo Kim Jaemin Yoo Kijung Shin GNN 25 10 0 05 Jun 2023
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance Jinwoo Kim Tien Dat Nguyen Ayhan Suleymanzade Hyeokjun An Seunghoon Hong 50 23 0 05 Jun 2023
InGram: Inductive Knowledge Graph Embedding via Relation Graphs Jaejun Lee Chanyoung Chung Joyce Jiyoung Whang GNN 27 39 0 31 May 2023
From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks Cai Zhou Xiyuan Wang Muhan Zhang 35 14 0 08 May 2023
Self-Attention in Colors: Another Take on Encoding Graph Structure in Transformers Romain Menegaux Emmanuel Jehanno Margot Selosse Julien Mairal 26 6 0 21 Apr 2023
What Do GNNs Actually Learn? Towards Understanding their Representations Giannis Nikolentzos Michail Chatzianastasis Michalis Vazirgiannis GNN AI4CE 18 0 0 21 Apr 2023
An Empirical Study of Realized GNN Expressiveness Yanbo Wang Muhan Zhang 42 10 0 16 Apr 2023
The expressive power of pooling in Graph Neural Networks F. Bianchi Veronica Lachi 19 29 0 04 Apr 2023
Understanding Expressivity of GNN in Rule Learning Haiquan Qiu Yongqi Zhang Yong Li Quanming Yao AI4CE 27 5 0 22 Mar 2023
Graph Positional Encoding via Random Feature Propagation Moshe Eliasof Fabrizio Frasca Beatrice Bevilacqua Eran Treister Gal Chechik Haggai Maron 32 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 33 1 0 02 Mar 2023
Some Might Say All You Need Is Sum Eran Rosenbluth Jan Toenshoff Martin Grohe 31 16 0 22 Feb 2023
Equivariant Polynomials for Graph Neural Networks Omri Puny Derek Lim B. Kiani Haggai Maron Y. Lipman 30 31 0 22 Feb 2023
Creating generalizable downstream graph models with random projections Anton Amirov Chris Quirk Jennifer Neville 11 1 0 17 Feb 2023
A Theory of Link Prediction via Relational Weisfeiler-Leman on Knowledge Graphs Xingyue Huang Miguel Romero .Ismail .Ilkan Ceylan Pablo Barceló 35 24 0 04 Feb 2023
Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation Types Jianfei Gao Yangze Zhou Jincheng Zhou Bruno Ribeiro 43 9 0 02 Feb 2023
Zero-One Laws of Graph Neural Networks Sam Adam-Day Theodor-Mihai Iliant .Ismail .Ilkan Ceylan GNN AI4CE 29 3 0 30 Jan 2023
WL meet VC Christopher Morris Floris Geerts Jan Tonshoff Martin Grohe 38 27 0 26 Jan 2023
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure Ryoma Sato 37 5 0 26 Jan 2023
State of the Art and Potentialities of Graph-level Learning Zhenyu Yang Ge Zhang Jia Wu Jian Yang Quan.Z Sheng ... Charu C. Aggarwal Hao Peng Wenbin Hu Edwin R. Hancock Pietro Lio GNN AI4CE 35 10 0 14 Jan 2023
A Generalization of ViT/MLP-Mixer to Graphs Xiaoxin He Bryan Hooi T. Laurent Adam Perold Yann LeCun Xavier Bresson 47 88 0 27 Dec 2022
Beyond 1-WL with Local Ego-Network Encodings Nurudin Alvarez-Gonzalez Andreas Kaltenbrunner Vicencc Gómez 38 5 0 27 Nov 2022
EDEN: A Plug-in Equivariant Distance Encoding to Beyond the 1-WL Test Chang-Shu Liu Yuwen Yang Yue Ding Hongtao Lu 38 1 0 19 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
Improving Graph Neural Networks with Learnable Propagation Operators Moshe Eliasof Lars Ruthotto Eran Treister 34 20 0 31 Oct 2022
Boosting the Cycle Counting Power of Graph Neural Networks with I $^2$ -GNNs Yinan Huang Xingang Peng Jianzhu Ma Muhan Zhang 84 47 0 22 Oct 2022
On Representing Mixed-Integer Linear Programs by Graph Neural Networks Ziang Chen Jialin Liu Xinshang Wang Jian Lu W. Yin AI4CE 32 16 0 19 Oct 2022
A Practical, Progressively-Expressive GNN Lingxiao Zhao Louis Härtel Neil Shah Leman Akoglu 32 17 0 18 Oct 2022