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A Survey on The Expressive Power of Graph Neural Networks

9 March 2020

Papers citing "A Survey on The Expressive Power of Graph Neural Networks"

50 / 107 papers shown

Title
On Representing Linear Programs by Graph Neural Networks Ziang Chen Jialin Liu Xinshang Wang Jian Lu W. Yin AI4CE 117 33 0 25 Sep 2022
From Local to Global: Spectral-Inspired Graph Neural Networks Ningyuan Huang Soledad Villar Carey E. Priebe Da Zheng Cheng-Fu Huang Lin F. Yang Vladimir Braverman 93 15 0 24 Sep 2022
Neural Graph Databases Maciej Besta Patrick Iff Florian Scheidl Kazuki Osawa Nikoli Dryden Michal Podstawski Tiancheng Chen Torsten Hoefler AI4CE 85 9 0 20 Sep 2022
Towards Better Generalization with Flexible Representation of Multi-Module Graph Neural Networks Hyungeun Lee Kijung Yoon AI4CE 58 2 0 14 Sep 2022
Efficient multi-relational network representation using primes K. Bougiatiotis George Giannakopoulos 76 1 0 14 Sep 2022
Neural Topological Ordering for Computation Graphs Mukul Gagrani Corrado Rainone Yang Yang Harris Teague Wonseok Jeon H. V. Hoof Weizhen Zeng P. Zappi Chris Lott Roberto Bondesan 80 12 0 13 Jul 2022
Wasserstein Graph Distance Based on $L_1$ -Approximated Tree Edit Distance between Weisfeiler-Lehman Subtrees Zhongxi Fang Jianming Huang Xun Su Hiroyuki Kasai 73 8 0 09 Jul 2022
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries Fabrizio Frasca Beatrice Bevilacqua Michael M. Bronstein Haggai Maron 83 133 0 22 Jun 2022
Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm Meng Liu Haiyang Yu Shuiwang Ji 56 1 0 04 Jun 2022
Graph-level Neural Networks: Current Progress and Future Directions Ge Zhang Hongzhi Zhang Jian Yang Shan Xue Wenbin Hu Chuan Zhou Hao Peng Quan.Z Sheng Charu C. Aggarwal GNN AI4CE 96 0 0 31 May 2022
Group-invariant max filtering Jameson Cahill Joseph W. Iverson D. Mixon Dan Packer 69 22 0 27 May 2022
Recipe for a General, Powerful, Scalable Graph Transformer Ladislav Rampášek Mikhail Galkin Vijay Prakash Dwivedi Anh Tuan Luu Guy Wolf Dominique Beaini 152 581 0 25 May 2022
Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis Maciej Besta Torsten Hoefler GNN 111 57 0 19 May 2022
Graph Neural Networks Designed for Different Graph Types: A Survey J. M. Thomas Alice Moallemy-Oureh Silvia Beddar-Wiesing Clara Holzhuter 130 30 0 06 Apr 2022
Graph Neural Networks in IoT: A Survey Guimin Dong Mingyue Tang Zhiyuan Wang Jiechao Gao Sikun Guo Lihua Cai Robert Gutierrez Brad Campbell Laura E. Barnes M. Boukhechba GNN AI4CE 93 107 0 29 Mar 2022
Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges S. Thais P. Calafiura G. Chachamis G. Dezoort Javier Mauricio Duarte S. Ganguly Michael Kagan D. Murnane Mark S. Neubauer K. Terao PINN AI4CE 121 31 0 23 Mar 2022
Twin Weisfeiler-Lehman: High Expressive GNNs for Graph Classification Zhaohui Wang Qi Cao Huawei Shen Bingbing Xu Xueqi Cheng 74 2 0 22 Mar 2022
Distribution Preserving Graph Representation Learning Chengsheng Mao Yuan Luo 49 0 0 27 Feb 2022
Sign and Basis Invariant Networks for Spectral Graph Representation Learning Derek Lim Joshua Robinson Lingxiao Zhao Tess E. Smidt S. Sra Haggai Maron Stefanie Jegelka 127 150 0 25 Feb 2022
1-WL Expressiveness Is (Almost) All You Need Markus Zopf 51 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 92 16 0 31 Jan 2022
A Theoretical Comparison of Graph Neural Network Extensions Pál András Papp Roger Wattenhofer 137 48 0 30 Jan 2022
A Short Tutorial on The Weisfeiler-Lehman Test And Its Variants Ningyuan Huang Soledad Villar 72 64 0 18 Jan 2022
Graph Kernel Neural Networks Luca Cosmo G. Minello Alessandro Bicciato M. Bronstein Emanuele Rodolà Luca Rossi A. Torsello GNN 70 22 0 14 Dec 2021
Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters Takanori Maehara Hoang NT 82 2 0 05 Nov 2021
Graph Neural Networks with Learnable Structural and Positional Representations Vijay Prakash Dwivedi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson GNN 292 330 0 15 Oct 2021
Understanding Pooling in Graph Neural Networks Daniele Grattarola Daniele Zambon F. Bianchi Cesare Alippi GNN FAtt AI4CE 459 95 0 11 Oct 2021
Equivariant Subgraph Aggregation Networks Beatrice Bevilacqua Fabrizio Frasca Derek Lim Balasubramaniam Srinivasan Chen Cai G. Balamurugan M. Bronstein Haggai Maron 130 180 0 06 Oct 2021
Graph Neural Networks: Methods, Applications, and Opportunities Lilapati Waikhom Ripon Patgiri GNN 95 42 0 24 Aug 2021
Generalization of graph network inferences in higher-order graphical models Yicheng Fei Xaq Pitkow 72 0 0 12 Jul 2021
Subgroup Generalization and Fairness of Graph Neural Networks Jiaqi Ma Junwei Deng Qiaozhu Mei 87 82 0 29 Jun 2021
Fea2Fea: Exploring Structural Feature Correlations via Graph Neural Networks Jiaqing Xie Rex Ying GNN 81 3 0 24 Jun 2021
Weisfeiler and Lehman Go Cellular: CW Networks Cristian Bodnar Fabrizio Frasca N. Otter Yu Guang Wang Pietro Lio Guido Montúfar M. Bronstein GNN 133 237 0 23 Jun 2021
On the approximation capability of GNNs in node classification/regression tasks Giuseppe Alessio D’Inverno Monica Bianchini M. Sampoli F. Scarselli 123 12 0 16 Jun 2021
Graph Neural Networks with Local Graph Parameters Pablo Barceló Floris Geerts Juan L. Reutter Maksimilian Ryschkov 85 66 0 12 Jun 2021
Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns Susheel Suresh Vinith Budde Jennifer Neville Pan Li Jianzhu Ma 85 136 0 11 Jun 2021
Motif Prediction with Graph Neural Networks Maciej Besta Raphael Grob Cesare Miglioli Nico Bernold Grzegorz Kwa'sniewski ... Raghavendra Kanakagiri Saleh Ashkboos Lukas Gianinazzi Nikoli Dryden Torsten Hoefler 87 38 0 26 May 2021
Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels Qingqing Long Yilun Jin Yi Wu Guojie Song 102 38 0 07 Apr 2021
Improving the Expressive Power of Graph Neural Network with Tinhofer Algorithm Alan J. X. Guo Qing-Hu Hou Ou Wu 43 0 0 05 Apr 2021
Size-Invariant Graph Representations for Graph Classification Extrapolations Beatrice Bevilacqua Yangze Zhou Bruno Ribeiro OOD 135 110 0 08 Mar 2021
SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks Bahare Fatemi Layla El Asri Seyed Mehran Kazemi GNN SSL 135 166 0 09 Feb 2021
Graph Neural Networks: Taxonomy, Advances and Trends Yu Zhou Haixia Zheng Xin Huang Shufeng Hao Dengao Li Jumin Zhao AI4TS 166 125 0 16 Dec 2020
Breaking the Expressive Bottlenecks of Graph Neural Networks Mingqi Yang Yanming Shen Heng Qi Baocai Yin 69 10 0 14 Dec 2020
On Graph Neural Networks versus Graph-Augmented MLPs Lei Chen Zhengdao Chen Joan Bruna 76 46 0 28 Oct 2020
A Simple Spectral Failure Mode for Graph Convolutional Networks Carey E. Priebe Cencheng Shen Ningyuan Huang Tianyi Chen GNN 26 7 0 25 Oct 2020
Incorporating Symbolic Domain Knowledge into Graph Neural Networks T. Dash A. Srinivasan Lovekesh Vig NAI 105 25 0 23 Oct 2020
Provenance Graph Kernel David Kohan Marzagão T. D. Huynh Ayah Helal Sean Baccas Luc Moreau 40 1 0 20 Oct 2020
The expressive power of kth-order invariant graph networks Floris Geerts 169 38 0 23 Jul 2020
Building powerful and equivariant graph neural networks with structural message-passing Clément Vignac Andreas Loukas P. Frossard 98 123 0 26 Jun 2020
Walk Message Passing Neural Networks and Second-Order Graph Neural Networks Floris Geerts 84 8 0 16 Jun 2020