Expressiveness and Approximation Properties of Graph Neural Networks

10 April 2022

Papers citing "Expressiveness and Approximation Properties of Graph Neural Networks"

50 / 51 papers shown

Title
Graph Representational Learning: When Does More Expressivity Hurt Generalization? Sohir Maskey Raffaele Paolino Fabian Jogl Gitta Kutyniok Johannes F. Lutzeyer 22 0 0 16 May 2025
Homomorphism Expressivity of Spectral Invariant Graph Neural Networks Jingchu Gai Yiheng Du Bohang Zhang Haggai Maron Liwei Wang 45 0 0 01 Mar 2025
ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective Yihong Chen Pushkar Mishra Luca Franceschi Pasquale Minervini Pontus Stenetorp Sebastian Riedel 67 20 0 17 Jan 2025
Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality Joshua Southern Yam Eitan Guy Bar-Shalom Michael M. Bronstein Haggai Maron Fabrizio Frasca 35 1 0 06 Jan 2025
Towards Bridging Generalization and Expressivity of Graph Neural Networks Shouheng Li Floris Geerts Dongwoo Kim Qing Wang 48 2 0 14 Oct 2024
Towards Dynamic Graph Neural Networks with Provably High-Order Expressive Power Zhe Wang Tianjian Zhao Zhen Zhang Jiawei Chen Sheng Zhou Yan Feng Chun Chen Can Wang 44 1 0 02 Oct 2024
Improving the Expressiveness of $K$ -hop Message-Passing GNNs by Injecting Contextualized Substructure Information Tianjun Yao Yiongxu Wang Kun Zhang Shangsong Liang 38 11 0 27 Jun 2024
Demystifying Higher-Order Graph Neural Networks Maciej Besta Florian Scheidl Lukas Gianinazzi S. Klaiman Jürgen Müller Torsten Hoefler 48 2 0 18 Jun 2024
Separation Power of Equivariant Neural Networks Marco Pacini Xiaowen Dong Bruno Lepri G. Santin 31 0 0 13 Jun 2024
Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs Ziang Chen Xiaohan Chen Jialin Liu Xinshang Wang Wotao Yin 43 4 0 09 Jun 2024
On the Expressive Power of Spectral Invariant Graph Neural Networks Bohang Zhang Lingxiao Zhao Haggai Maron 56 8 0 06 Jun 2024
Bundle Neural Networks for message diffusion on graphs Jacob Bamberger Federico Barbero Xiaowen Dong Michael M. Bronstein 41 1 0 24 May 2024
Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning Raffaele Paolino Sohir Maskey Pascal Welke Gitta Kutyniok 33 2 0 20 Mar 2024
Local Vertex Colouring Graph Neural Networks Shouheng Li Dongwoo Kim Qing Wang 63 1 0 10 Mar 2024
Almost Surely Asymptotically Constant Graph Neural Networks Sam Adam-Day Michael Benedikt .Ismail .Ilkan Ceylan Ben Finkelshtein GNN 71 2 0 06 Mar 2024
Clifford Group Equivariant Simplicial Message Passing Networks Cong Liu David Ruhe Floor Eijkelboom Patrick Forré 27 14 0 15 Feb 2024
Homomorphism Counts for Graph Neural Networks: All About That Basis Emily Jin Michael M. Bronstein .Ismail .Ilkan Ceylan Matthias Lanzinger 26 11 0 13 Feb 2024
Weisfeiler-Leman at the margin: When more expressivity matters Billy J. Franks Christopher Morris A. Velingker Floris Geerts 58 10 0 12 Feb 2024
Rethinking the Capacity of Graph Neural Networks for Branching Strategy Ziang Chen Jialin Liu Xiaohan Chen Xinshang Wang Wotao Yin 53 3 0 11 Feb 2024
Future Directions in the Theory of Graph Machine Learning Christopher Morris Fabrizio Frasca Nadav Dym Haggai Maron .Ismail .Ilkan Ceylan Ron Levie Derek Lim Michael M. Bronstein Martin Grohe Stefanie Jegelka AI4CE 40 5 0 03 Feb 2024
Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs Yeyuan Chen Dingmin Wang 27 0 0 03 Nov 2023
Can strong structural encoding reduce the importance of Message Passing? Floor Eijkelboom Erik J. Bekkers Michael M. Bronstein Francesco Di Giovanni University of Amsterdam 27 2 0 22 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 40 19 0 16 Aug 2023
On the power of graph neural networks and the role of the activation function Sammy Khalife A. Basu 24 7 0 10 Jul 2023
Path Neural Networks: Expressive and Accurate Graph Neural Networks Gaspard Michel Giannis Nikolentzos J. Lutzeyer Michalis Vazirgiannis GNN 23 26 0 09 Jun 2023
Fine-grained Expressivity of Graph Neural Networks Jan Böker Ron Levie Ningyuan Huang Soledad Villar Christopher Morris 30 20 0 06 Jun 2023
How does over-squashing affect the power of GNNs? Francesco Di Giovanni T. Konstantin Rusch Michael M. Bronstein Andreea Deac Marc Lackenby Siddhartha Mishra Petar Velivcković 36 34 0 06 Jun 2023
An Empirical Study of Realized GNN Expressiveness Yanbo Wang Muhan Zhang 42 10 0 16 Apr 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
WL meet VC Christopher Morris Floris Geerts Jan Tonshoff Martin Grohe 38 27 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 43 10 0 14 Jan 2023
Homophily modulates double descent generalization in graph convolution networks Chengzhi Shi Liming Pan Hong Hu Ivan Dokmanić 37 9 0 26 Dec 2022
Weisfeiler and Leman Go Relational Pablo Barceló Mikhail Galkin Christopher Morris Miguel Romero Orth GNN 48 27 0 30 Nov 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
EDEN: A Plug-in Equivariant Distance Encoding to Beyond the 1-WL Test Chang-Shu Liu Yuwen Yang Yue Ding Hongtao Lu 40 1 0 19 Nov 2022
On Representing Mixed-Integer Linear Programs by Graph Neural Networks Ziang Chen Jialin Liu Xinshang Wang Jian Lu W. Yin AI4CE 34 16 0 19 Oct 2022
A Practical, Progressively-Expressive GNN Lingxiao Zhao Louis Härtel Neil Shah Leman Akoglu 32 17 0 18 Oct 2022
Linkless Link Prediction via Relational Distillation Zhichun Guo William Shiao Shichang Zhang Yozen Liu Nitesh V. Chawla Neil Shah Tong Zhao 27 41 0 11 Oct 2022
On Representing Linear Programs by Graph Neural Networks Ziang Chen Jialin Liu Xinshang Wang Jian Lu W. Yin AI4CE 60 31 0 25 Sep 2022
Generalizing Downsampling from Regular Data to Graphs D. Bacciu A. Conte Francesco Landolfi 45 8 0 06 Aug 2022
Ordered Subgraph Aggregation Networks Chao Qian Gaurav Rattan Floris Geerts Christopher Morris Mathias Niepert 51 57 0 22 Jun 2022
Agent-based Graph Neural Networks Karolis Martinkus Pál András Papp Benedikt Schesch Roger Wattenhofer LLMAG GNN 39 17 0 22 Jun 2022
Lower and Upper Bounds for Numbers of Linear Regions of Graph Convolutional Networks Hao Chen Yu Wang Huan Xiong GNN 16 6 0 01 Jun 2022
Representation Power of Graph Neural Networks: Improved Expressivity via Algebraic Analysis Charilaos I. Kanatsoulis Alejandro Ribeiro 39 4 0 19 May 2022
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks Christopher Morris Gaurav Rattan Sandra Kiefer Siamak Ravanbakhsh 50 40 0 25 Mar 2022
On the expressive power of message-passing neural networks as global feature map transformers Floris Geerts Jasper Steegmans Jan Van den Bussche 22 6 0 17 Mar 2022
Permutation Invariant Representations with Applications to Graph Deep Learning R. Balan Naveed Haghani M. Singh 31 25 0 14 Mar 2022
What Functions Can Graph Neural Networks Generate? Mohammad Fereydounian Hamed Hassani Amin Karbasi 33 4 0 17 Feb 2022