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Relational Pooling for Graph Representations

6 March 2019

R. Murphy

Balasubramaniam Srinivasan

Papers citing "Relational Pooling for Graph Representations"

50 / 167 papers shown

Title
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance Jinwoo Kim Tien Dat Nguyen Ayhan Suleymanzade Hyeokjun An Seunghoon Hong 100 24 0 05 Jun 2023
Size Generalization of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective Gao Li Danai Koutra Yujun Yan 31 1 0 24 May 2023
From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks Cai Zhou Xiyuan Wang Muhan Zhang 66 15 0 08 May 2023
What Do GNNs Actually Learn? Towards Understanding their Representations Giannis Nikolentzos Michail Chatzianastasis Michalis Vazirgiannis GNN AI4CE 63 1 0 21 Apr 2023
An Empirical Study of Realized GNN Expressiveness Yanbo Wang Muhan Zhang 93 14 0 16 Apr 2023
An Efficient Subgraph GNN with Provable Substructure Counting Power Zuoyu Yan Junru Zhou Liangcai Gao Zhi Tang Muhan Zhang GNN 84 14 0 19 Mar 2023
Exphormer: Sparse Transformers for Graphs Hamed Shirzad A. Velingker B. Venkatachalam Danica J. Sutherland A. Sinop 76 118 0 10 Mar 2023
Are More Layers Beneficial to Graph Transformers? Haiteng Zhao Shuming Ma Dongdong Zhang Zhi-Hong Deng Furu Wei 67 14 0 01 Mar 2023
Equivariant Polynomials for Graph Neural Networks Omri Puny Derek Lim B. Kiani Haggai Maron Y. Lipman 82 33 0 22 Feb 2023
Diffusion Probabilistic Models for Structured Node Classification Hyosoon Jang Seonghyun Park Sangwoo Mo SungSoo Ahn DiffM 77 3 0 21 Feb 2023
G-Signatures: Global Graph Propagation With Randomized Signatures Bernhard Schafl Lukas Gruber Johannes Brandstetter Sepp Hochreiter 146 2 0 17 Feb 2023
Attending to Graph Transformers Luis Muller Mikhail Galkin Christopher Morris Ladislav Rampášek 97 93 0 08 Feb 2023
Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation Types Jianfei Gao Yangze Zhou Jincheng Zhou Bruno Ribeiro 105 13 0 02 Feb 2023
WL meet VC Christopher Morris Floris Geerts Jan Tönshoff Martin Grohe 114 27 0 26 Jan 2023
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure Ryoma Sato 95 6 0 26 Jan 2023
State of the Art and Potentialities of Graph-level Learning Zhenyu Yang Ge Zhang Hongzhi Zhang Jian Yang Quan.Z Sheng ... Charu C. Aggarwal Hao Peng Wenbin Hu Edwin R. Hancock Pietro Lio GNN AI4CE 125 15 0 14 Jan 2023
A Generalization of ViT/MLP-Mixer to Graphs Xiaoxin He Bryan Hooi T. Laurent Adam Perold Yann LeCun Xavier Bresson 115 98 0 27 Dec 2022
Bridging Graph Position Encodings for Transformers with Weighted Graph-Walking Automata Patrick M. Soga David Chiang 146 0 0 13 Dec 2022
Integration of Pre-trained Protein Language Models into Geometric Deep Learning Networks Fang Wu Yujun Tao Dragomir R. Radev Jinbo Xu Stan Z. Li AI4CE 86 34 0 07 Dec 2022
Invariance-Aware Randomized Smoothing Certificates Jan Schuchardt Stephan Günnemann AAML 56 6 0 25 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 83 21 0 06 Nov 2022
Weisfeiler and Leman go Hyperbolic: Learning Distance Preserving Node Representations Giannis Nikolentzos Michail Chatzianastasis Michalis Vazirgiannis 53 8 0 04 Nov 2022
Boosting the Cycle Counting Power of Graph Neural Networks with I $^2$ -GNNs Yinan Huang Xingang Peng Jianzhu Ma Muhan Zhang 132 49 0 22 Oct 2022
A Practical, Progressively-Expressive GNN Lingxiao Zhao Louis Härtel Neil Shah Leman Akoglu 85 18 0 18 Oct 2022
Memory-Augmented Graph Neural Networks: A Brain-Inspired Review Guixiang Ma Vy A. Vo Ted Willke Nesreen Ahmed 74 1 0 22 Sep 2022
LogGD:Detecting Anomalies from System Logs by Graph Neural Networks Yongzhen Xie Hongyu Zhang M. Babar AI4TS 81 20 0 16 Sep 2022
Affinity-Aware Graph Networks A. Velingker A. Sinop Ira Ktena Petar Velickovic Sreenivas Gollapudi GNN 107 17 0 23 Jun 2022
Ordered Subgraph Aggregation Networks Chao Qian Gaurav Rattan Floris Geerts Christopher Morris Mathias Niepert 121 58 0 22 Jun 2022
Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm Meng Liu Haiyang Yu Shuiwang Ji 56 1 0 04 Jun 2022
Shortest Path Networks for Graph Property Prediction Ralph Abboud Radoslav Dimitrov .Ismail .Ilkan Ceylan GNN 109 49 0 02 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
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs Yangze Zhou Gitta Kutyniok Bruno Ribeiro OODD AI4CE 160 39 0 30 May 2022
Going Deeper into Permutation-Sensitive Graph Neural Networks Zhongyu Huang Yingheng Wang Chaozhuo Li Huiguang He 78 32 0 28 May 2022
How Powerful are K-hop Message Passing Graph Neural Networks Jiarui Feng Yixin Chen Fuhai Li Anindya Sarkar Muhan Zhang 77 108 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 169 581 0 25 May 2022
Representation Power of Graph Neural Networks: Improved Expressivity via Algebraic Analysis Charilaos I. Kanatsoulis Alejandro Ribeiro 55 4 0 19 May 2022
Theory of Graph Neural Networks: Representation and Learning Stefanie Jegelka GNN AI4CE 93 70 0 16 Apr 2022
Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities Chuang Liu Yibing Zhan Hongzhi Zhang Chang Li Bo Du Wenbin Hu Tongliang Liu Dacheng Tao GNN AI4CE 112 82 0 15 Apr 2022
A Survey on Graph Representation Learning Methods Shima Khoshraftar A. An GNN AI4TS 103 124 0 04 Apr 2022
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks Christopher Morris Gaurav Rattan Sandra Kiefer Siamak Ravanbakhsh 129 40 0 25 Mar 2022
Graph Representation Learning with Individualization and Refinement Mohammed Haroon Dupty W. Lee 50 3 0 17 Mar 2022
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks Hongya Wang Haoteng Yin Muhan Zhang Pan Li 116 115 0 01 Mar 2022
Message passing all the way up Petar Velickovic 175 66 0 22 Feb 2022
Molecular Representation Learning via Heterogeneous Motif Graph Neural Networks Zhaoning Yu Hongyang Gao 73 45 0 01 Feb 2022
Revisiting Transformation Invariant Geometric Deep Learning: Are Initial Representations All You Need? Ziwei Zhang Xin Eric Wang Zeyang Zhang Peng Cui Wenwu Zhu 3DPC 53 6 0 23 Dec 2021
Weisfeiler and Leman go Machine Learning: The Story so far Christopher Morris Y. Lipman Haggai Maron Bastian Rieck Nils M. Kriege Martin Grohe Matthias Fey Karsten Borgwardt GNN 127 118 0 18 Dec 2021
Set Twister for Single-hop Node Classification Yangze Zhou Vinayak A. Rao Bruno Ribeiro 60 0 0 17 Dec 2021
A systematic approach to random data augmentation on graph neural networks Billy Joe Franks Markus Anders Marius Kloft Pascal Schweitzer OOD AAML 18 0 0 08 Dec 2021
Nested Graph Neural Networks Muhan Zhang Pan Li 88 169 0 25 Oct 2021
Graph Filtration Kernels Till Hendrik Schulz Pascal Welke Stefanie Wrobel 60 13 0 22 Oct 2021