Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting

16 June 2020

Papers citing "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting"

50 / 262 papers shown

Title
Are More Layers Beneficial to Graph Transformers? Haiteng Zhao Shuming Ma Dongdong Zhang Zhi-Hong Deng Furu Wei 27 12 0 01 Mar 2023
Equivariant Polynomials for Graph Neural Networks Omri Puny Derek Lim B. Kiani Haggai Maron Y. Lipman 28 31 0 22 Feb 2023
On the Expressivity of Persistent Homology in Graph Learning Bastian Alexander Rieck Bastian Rieck 19 13 0 20 Feb 2023
Is Distance Matrix Enough for Geometric Deep Learning? Zian Li Xiyuan Wang Yinan Huang Muhan Zhang 37 17 0 11 Feb 2023
Attending to Graph Transformers Luis Muller Mikhail Galkin Christopher Morris Ladislav Rampášek 49 86 0 08 Feb 2023
Learning to Count Isomorphisms with Graph Neural Networks Xingtong Yu Zemin Liu Yuan Fang Xinming Zhang GNN 32 15 0 07 Feb 2023
Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing Yunchong Song Cheng Zhou Xinbing Wang Zhouhan Lin 32 62 0 03 Feb 2023
Curvature Filtrations for Graph Generative Model Evaluation Joshua Southern Jeremy Wayland Michael M. Bronstein Bastian Alexander Rieck 23 14 0 30 Jan 2023
Continual Graph Learning: A Survey Qiao Yuan S. Guan Pin Ni Tianlun Luo Ka Lok Man Prudence W. H. Wong Victor I. Chang CLL 24 14 0 28 Jan 2023
Graph Scattering beyond Wavelet Shackles Christian Koke Gitta Kutyniok 18 4 0 26 Jan 2023
WL meet VC Christopher Morris Floris Geerts Jan Tonshoff Martin Grohe 38 27 0 26 Jan 2023
Introducing Expertise Logic into Graph Representation Learning from A Causal Perspective Hang Gao Jiangmeng Li Jingyao Wang Hui Xiong Xingzhe Su Feng Wu Changwen Zheng Gang Hua 39 0 0 20 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 Network Science perspective of Graph Convolutional Networks: A survey Mingshan Jia Bogdan Gabrys Katarzyna Musial GNN 32 7 0 12 Jan 2023
t-SMILES: A Scalable Fragment-based Molecular Representation Framework for De Novo Molecule Generation Juan-Ni Wu Tong Wang Yue (Eleanor) Chen Li-Juan Tang Hai-Long Wu Ru-Qin Yu 19 0 0 04 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
TIDE: Time Derivative Diffusion for Deep Learning on Graphs M. Behmanesh Maximilian Krahn M. Ovsjanikov DiffM GNN 24 9 0 05 Dec 2022
GrannGAN: Graph annotation generative adversarial networks Yoann Boget Magda Gregorova Alexandros Kalousis GAN 15 0 0 01 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
Beyond 1-WL with Local Ego-Network Encodings Nurudin Alvarez-Gonzalez Andreas Kaltenbrunner Vicencc Gómez 38 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
Towards Better Out-of-Distribution Generalization of Neural Algorithmic Reasoning Tasks Sadegh Mahdavi Kevin Swersky Thomas Kipf Milad Hashemi Christos Thrampoulidis Renjie Liao LRM OOD NAI 45 25 0 01 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
A Practical, Progressively-Expressive GNN Lingxiao Zhao Louis Härtel Neil Shah L. Akoglu 32 17 0 18 Oct 2022
Test-Time Training for Graph Neural Networks Yiqi Wang Chaozhuo Li Wei Jin Rui Li Jianan Zhao Jiliang Tang Xing Xie OOD 27 14 0 17 Oct 2022
Uplifting Message Passing Neural Network with Graph Original Information Xiao Liu Lijun Zhang Hui Guan GNN 26 2 0 08 Oct 2022
Expander Graph Propagation Andreea Deac Marc Lackenby Petar Velivcković 96 52 0 06 Oct 2022
Graph Neural Networks for Link Prediction with Subgraph Sketching B. Chamberlain S. Shirobokov Emanuele Rossi Fabrizio Frasca Thomas Markovich Nils Y. Hammerla Michael M. Bronstein Max Hansmire 46 77 0 30 Sep 2022
Provably expressive temporal graph networks Amauri Souza Diego Mesquita Samuel Kaski Vikas K. Garg 89 54 0 29 Sep 2022
Cell Attention Networks Lorenzo Giusti Claudio Battiloro Lucia Testa P. Lorenzo S. Sardellitti Sergio Barbarossa 3DPC GNN 141 32 0 16 Sep 2022
Models and Benchmarks for Representation Learning of Partially Observed Subgraphs Dongkwan Kim Jiho Jin Jaimeen Ahn Alice H. Oh 34 3 0 01 Sep 2022
pathGCN: Learning General Graph Spatial Operators from Paths Moshe Eliasof E. Haber Eran Treister 3DPC GNN 23 26 0 15 Jul 2022
Affinity-Aware Graph Networks A. Velingker A. Sinop Ira Ktena Petar Velickovic Sreenivas Gollapudi GNN 50 16 0 23 Jun 2022
Ordered Subgraph Aggregation Networks Chao Qian Gaurav Rattan Floris Geerts Christopher Morris Mathias Niepert 41 57 0 22 Jun 2022
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries Fabrizio Frasca Beatrice Bevilacqua Michael M. Bronstein Haggai Maron 35 125 0 22 Jun 2022
Agent-based Graph Neural Networks Karolis Martinkus Pál András Papp Benedikt Schesch Roger Wattenhofer LLMAG GNN 29 17 0 22 Jun 2022
Long Range Graph Benchmark Vijay Prakash Dwivedi Ladislav Rampášek Mikhail Galkin Alipanah Parviz Guy Wolf A. Luu Dominique Beaini 26 195 0 16 Jun 2022
Evaluating Graph Generative Models with Contrastively Learned Features Hamed Shirzad Kaveh Hassani Danica J. Sutherland 16 7 0 13 Jun 2022
Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm Meng Liu Haiyang Yu Shuiwang Ji 33 1 0 04 Jun 2022
Graph Neural Networks with Precomputed Node Features Béni Egressy Roger Wattenhofer 17 2 0 01 Jun 2022
Automatic Relation-aware Graph Network Proliferation Shaofei Cai Liang Li Xinzhe Han Jiebo Luo Zhengjun Zha Qingming Huang GNN 45 8 0 31 May 2022
Graph-level Neural Networks: Current Progress and Future Directions Ge Zhang Jia Wu Jian Yang Shan Xue Wenbin Hu Chuan Zhou Hao Peng Quan.Z Sheng Charu C. Aggarwal GNN AI4CE 43 0 0 31 May 2022
Going Deeper into Permutation-Sensitive Graph Neural Networks Zhongyu Huang Yingheng Wang Chaozhuo Li Huiguang He 16 31 0 28 May 2022
ES-GNN: Generalizing Graph Neural Networks Beyond Homophily with Edge Splitting Jingwei Guo Kaizhu Huang Rui Zhang Xinping Yi AAML 28 4 0 27 May 2022
How Powerful are K-hop Message Passing Graph Neural Networks Jiarui Feng Yixin Chen Fuhai Li Anindya Sarkar Muhan Zhang 14 100 0 26 May 2022
Recipe for a General, Powerful, Scalable Graph Transformer Ladislav Rampášek Mikhail Galkin Vijay Prakash Dwivedi A. Luu Guy Wolf Dominique Beaini 57 515 0 25 May 2022
Representation Power of Graph Neural Networks: Improved Expressivity via Algebraic Analysis Charilaos I. Kanatsoulis Alejandro Ribeiro 33 4 0 19 May 2022
GRAPHYP: A Scientific Knowledge Graph with Manifold Subnetworks of Communities. Detection of Scholarly Disputes in Adversarial Information Routes Renaud Fabre Otmane Azeroual P. Bellot Joachim Schöpfel D. Egret 8 0 0 03 May 2022
Graph Anisotropic Diffusion Ahmed A. A. Elhag Gabriele Corso Hannes Stärk Michael M. Bronstein DiffM GNN 17 0 0 30 Apr 2022