What graph neural networks cannot learn: depth vs width

6 July 2019

Papers citing "What graph neural networks cannot learn: depth vs width"

50 / 78 papers shown

Title
Relational Graph Transformer Vijay Prakash Dwivedi Sri Jaladi Yangyi Shen Federico López Charilaos I. Kanatsoulis Rishi Puri Matthias Fey Jure Leskovec 32 0 0 16 May 2025
Towards Invariance to Node Identifiers in Graph Neural Networks Maya Bechler-Speicher Moshe Eliasof Carola-Bibiane Schönlieb Ran Gilad-Bachrach Amir Globerson 72 1 0 20 Feb 2025
Homomorphism Counts as Structural Encodings for Graph Learning Linus Bao Emily Jin Michael M. Bronstein .Ismail .Ilkan Ceylan Matthias Lanzinger 34 1 0 24 Oct 2024
Mesh-Informed Reduced Order Models for Aneurysm Rupture Risk Prediction Giuseppe Alessio DÍnverno Saeid Moradizadeh Sajad Salavatidezfouli Pasquale Claudio Africa G. Rozza AI4CE 46 0 0 04 Oct 2024
Revisiting Random Walks for Learning on Graphs Jinwoo Kim Olga Zaghen Ayhan Suleymanzade Youngmin Ryou Seunghoon Hong 73 0 0 01 Jul 2024
Lightweight Spatial Modeling for Combinatorial Information Extraction From Documents Yanfei Dong Lambert Deng Jiazheng Zhang Xiaodong Yu Ting Lin Francesco Gelli Soujanya Poria W. Lee 45 0 0 08 May 2024
A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms Raffaele Marino L. Buffoni Bogdan Zavalnij GNN 45 5 0 13 Mar 2024
Graph Transformers without Positional Encodings Ayush Garg 29 0 0 31 Jan 2024
PF-GNN: Differentiable particle filtering based approximation of universal graph representations Mohammed Haroon Dupty Yanfei Dong W. Lee 28 13 0 31 Jan 2024
Isomorphic-Consistent Variational Graph Auto-Encoders for Multi-Level Graph Representation Learning Hanxuan Yang Qingchao Kong Wenji Mao BDL 33 0 0 09 Dec 2023
Going beyond persistent homology using persistent homology Johanna Immonen Amauri H. Souza Vikas K. Garg 46 9 0 10 Nov 2023
Cooperative Graph Neural Networks Ben Finkelshtein Xingyue Huang Michael M. Bronstein .Ismail .Ilkan Ceylan GNN 47 20 0 02 Oct 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 45 20 0 16 Aug 2023
Weisfeiler and Leman Go Measurement Modeling: Probing the Validity of the WL Test Arjun Subramonian Adina Williams Maximilian Nickel Yizhou Sun Levent Sagun 41 0 0 11 Jul 2023
Graph Inductive Biases in Transformers without Message Passing Liheng Ma Chen Lin Derek Lim Adriana Romero Soriano P. Dokania Mark Coates Philip Torr Ser-Nam Lim AI4CE 51 85 0 27 May 2023
Descriptive complexity for distributed computing with circuits Veeti Ahvonen Damian Heiman L. Hella Antti Kuusisto 31 4 0 08 Mar 2023
Equivariant Polynomials for Graph Neural Networks Omri Puny Derek Lim B. Kiani Haggai Maron Y. Lipman 35 31 0 22 Feb 2023
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure Ryoma Sato 42 5 0 26 Jan 2023
Everything is Connected: Graph Neural Networks Petar Velickovic GNN AI4CE 25 179 0 19 Jan 2023
A Generalization of ViT/MLP-Mixer to Graphs Xiaoxin He Bryan Hooi T. Laurent Adam Perold Yann LeCun Xavier Bresson 49 88 0 27 Dec 2022
Learning Graph Algorithms With Recurrent Graph Neural Networks Florian Grötschla Joël Mathys Roger Wattenhofer GNN 24 6 0 09 Dec 2022
On the Ability of Graph Neural Networks to Model Interactions Between Vertices Noam Razin Tom Verbin Nadav Cohen 23 10 0 29 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 44 21 0 06 Nov 2022
Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network Yi Yi Xu Wan Kangfei Zhao Ou-Yang Le Pei-Ying Zhao 34 1 0 27 Oct 2022
Boosting the Cycle Counting Power of Graph Neural Networks with I $^2$ -GNNs Yinan Huang Xingang Peng Jianzhu Ma Muhan Zhang 84 46 0 22 Oct 2022
Low-Rank Representations Towards Classification Problem of Complex Networks Murat Çelik Ali Baran Tasdemir Lale Özkahya GNN 21 0 0 20 Oct 2022
On Classification Thresholds for Graph Attention with Edge Features K. Fountoulakis Dake He Silvio Lattanzi Bryan Perozzi Anton Tsitsulin Shenghao Yang GNN 35 6 0 18 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 36 9 0 08 Oct 2022
Provably expressive temporal graph networks Amauri Souza Diego Mesquita Samuel Kaski Vikas K. Garg 89 55 0 29 Sep 2022
On Representing Linear Programs by Graph Neural Networks Ziang Chen Jialin Liu Xinshang Wang Jian Lu W. Yin AI4CE 64 31 0 25 Sep 2022
On the Privacy Risks of Cell-Based NAS Architectures Haiping Huang Zhikun Zhang Yun Shen Michael Backes Qi Li Yang Zhang 35 7 0 04 Sep 2022
Agent-based Graph Neural Networks Karolis Martinkus Pál András Papp Benedikt Schesch Roger Wattenhofer LLMAG GNN 44 17 0 22 Jun 2022
Universally Expressive Communication in Multi-Agent Reinforcement Learning Matthew Morris Thomas D. Barrett Arnu Pretorius 26 4 0 14 Jun 2022
Shortest Path Networks for Graph Property Prediction Ralph Abboud Radoslav Dimitrov .Ismail .Ilkan Ceylan GNN 31 46 0 02 Jun 2022
DT+GNN: A Fully Explainable Graph Neural Network using Decision Trees Peter Müller Lukas Faber Karolis Martinkus Roger Wattenhofer 45 8 0 26 May 2022
Recipe for a General, Powerful, Scalable Graph Transformer Ladislav Rampášek Mikhail Galkin Vijay Prakash Dwivedi Anh Tuan Luu Guy Wolf Dominique Beaini 83 527 0 25 May 2022
Not too little, not too much: a theoretical analysis of graph (over)smoothing Nicolas Keriven 57 91 0 24 May 2022
Theory of Graph Neural Networks: Representation and Learning Stefanie Jegelka GNN AI4CE 38 68 0 16 Apr 2022
Graph Neural Networks for Wireless Communications: From Theory to Practice Yifei Shen Jun Zhang Shenghui Song Khaled B. Letaief GNN AI4CE 40 112 0 21 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 50 65 0 09 Mar 2022
Message passing all the way up Petar Velickovic 121 64 0 22 Feb 2022
A Theoretical Comparison of Graph Neural Network Extensions Pál András Papp Roger Wattenhofer 103 47 0 30 Jan 2022
Classic Graph Structural Features Outperform Factorization-Based Graph Embedding Methods on Community Labeling Andrew Stolman Caleb C. Levy C. Seshadhri Aneesh Sharma GNN 16 11 0 20 Jan 2022
A Short Tutorial on The Weisfeiler-Lehman Test And Its Variants Ningyuan Huang Soledad Villar 24 63 0 18 Jan 2022
Equivariant Quantum Graph Circuits Péter Mernyei K. Meichanetzidis .Ismail .Ilkan Ceylan 44 8 0 10 Dec 2021
OOD-GNN: Out-of-Distribution Generalized Graph Neural Network Haoyang Li Xin Eric Wang Ziwei Zhang Wenwu Zhu OODD OOD 41 97 0 07 Dec 2021
Learning Connectivity with Graph Convolutional Networks for Skeleton-based Action Recognition H. Sahbi GNN 48 27 0 06 Dec 2021
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks Pál András Papp Karolis Martinkus Lukas Faber Roger Wattenhofer GNN 28 139 0 11 Nov 2021
On Provable Benefits of Depth in Training Graph Convolutional Networks Weilin Cong M. Ramezani M. Mahdavi 32 74 0 28 Oct 2021
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization Mucong Ding Kezhi Kong Jingling Li Chen Zhu John P. Dickerson Furong Huang Tom Goldstein GNN MQ 33 47 0 27 Oct 2021