Relational Pooling for Graph Representations

6 March 2019

R. Murphy

Balasubramaniam Srinivasan

Papers citing "Relational Pooling for Graph Representations"

50 / 61 papers shown

Title
Towards Invariance to Node Identifiers in Graph Neural Networks Maya Bechler-Speicher Moshe Eliasof Carola-Bibiane Schönlieb Ran Gilad-Bachrach Amir Globerson 56 1 0 20 Feb 2025
Optimality of Message-Passing Architectures for Sparse Graphs Aseem Baranwal K. Fountoulakis Aukosh Jagannath 81 11 0 10 Jan 2025
Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings Billy Joe Franks Moshe Eliasof Semih Cantürk Guy Wolf Carola-Bibiane Schönlieb Sophie Fellenz Marius Kloft AI4CE 76 0 0 10 Dec 2024
Revisiting Random Walks for Learning on Graphs Jinwoo Kim Olga Zaghen Ayhan Suleymanzade Youngmin Ryou Seunghoon Hong 59 0 0 01 Jul 2024
KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning Roman Bresson Giannis Nikolentzos G. Panagopoulos Michail Chatzianastasis Jun Pang Michalis Vazirgiannis 65 42 0 26 Jun 2024
Baking Symmetry into GFlowNets George Ma Emmanuel Bengio Yoshua Bengio Dinghuai Zhang 45 8 0 08 Jun 2024
Contextualized Messages Boost Graph Representations Brian Godwin Lim Galvin Brice Lim Renzo Roel Tan Kazushi Ikeda AI4CE 70 1 0 19 Mar 2024
Topology-Informed Graph Transformer Yuncheol Choi Sun Woo Park Minho Lee Youngho Woo 21 3 0 03 Feb 2024
CktGNN: Circuit Graph Neural Network for Electronic Design Automation Zehao Dong Weidong Cao Muhan Zhang Dacheng Tao Yixin Chen Xuan Zhang GNN 34 30 0 31 Aug 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
Prot2Text: Multimodal Protein's Function Generation with GNNs and Transformers Hadi Abdine Michail Chatzianastasis Costas Bouyioukos Michalis Vazirgiannis 28 40 0 25 Jul 2023
Supervised Attention Using Homophily in Graph Neural Networks Michail Chatzianastasis Giannis Nikolentzos Michalis Vazirgiannis GNN 16 0 0 11 Jul 2023
Expectation-Complete Graph Representations with Homomorphisms Pascal Welke Maximilian Thiessen Fabian Jogl Thomas Gärtner 18 6 0 09 Jun 2023
Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman Jiarui Feng Lecheng Kong Hao Liu Dacheng Tao Fuhai Li Muhan Zhang Yixin Chen 44 10 0 05 Jun 2023
From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks Cai Zhou Xiyuan Wang Muhan Zhang 28 14 0 08 May 2023
An Empirical Study of Realized GNN Expressiveness Yanbo Wang Muhan Zhang 39 10 0 16 Apr 2023
Equivariant Polynomials for Graph Neural Networks Omri Puny Derek Lim B. Kiani Haggai Maron Y. Lipman 24 31 0 22 Feb 2023
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure Ryoma Sato 31 5 0 26 Jan 2023
A Generalization of ViT/MLP-Mixer to Graphs Xiaoxin He Bryan Hooi T. Laurent Adam Perold Yann LeCun Xavier Bresson 36 88 0 27 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 27 32 0 07 Dec 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
Boosting the Cycle Counting Power of Graph Neural Networks with I $^2$ -GNNs Yinan Huang Xingang Peng Jianzhu Ma Muhan Zhang 81 47 0 22 Oct 2022
Shortest Path Networks for Graph Property Prediction Ralph Abboud Radoslav Dimitrov .Ismail .Ilkan Ceylan GNN 27 44 0 02 Jun 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 38 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 73 37 0 30 May 2022
Recipe for a General, Powerful, Scalable Graph Transformer Ladislav Rampášek Mikhail Galkin Vijay Prakash Dwivedi A. Luu Guy Wolf Dominique Beaini 57 514 0 25 May 2022
Theory of Graph Neural Networks: Representation and Learning Stefanie Jegelka GNN AI4CE 33 68 0 16 Apr 2022
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks Christopher Morris Gaurav Rattan Sandra Kiefer Siamak Ravanbakhsh 44 39 0 25 Mar 2022
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks Hongya Wang Haoteng Yin Muhan Zhang Pan Li 35 107 0 01 Mar 2022
Graph Filtration Kernels Till Hendrik Schulz Pascal Welke Stefanie Wrobel 24 12 0 22 Oct 2021
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness Lingxiao Zhao Wei Jin L. Akoglu Neil Shah GNN 24 160 0 07 Oct 2021
Equivariant Subgraph Aggregation Networks Beatrice Bevilacqua Fabrizio Frasca Derek Lim Balasubramaniam Srinivasan Chen Cai G. Balamurugan M. Bronstein Haggai Maron 48 174 0 06 Oct 2021
Permute Me Softly: Learning Soft Permutations for Graph Representations Giannis Nikolentzos George Dasoulas Michalis Vazirgiannis GNN 34 9 0 05 Oct 2021
Reconstruction for Powerful Graph Representations Leonardo Cotta Christopher Morris Bruno Ribeiro AI4CE 127 78 0 01 Oct 2021
Graph Neural Networks for Graph Drawing Matteo Tiezzi Gabriele Ciravegna Marco Gori 21 20 0 21 Sep 2021
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study Tianlong Chen Kaixiong Zhou Keyu Duan Wenqing Zheng Peihao Wang Xia Hu Zhangyang Wang AAML GNN 27 61 0 24 Aug 2021
Global Self-Attention as a Replacement for Graph Convolution Md Shamim Hussain Mohammed J. Zaki D. Subramanian ViT 31 121 0 07 Aug 2021
Simple GNN Regularisation for 3D Molecular Property Prediction & Beyond Jonathan Godwin Michael Schaarschmidt Alex Gaunt Alvaro Sanchez-Gonzalez Yulia Rubanova Petar Velivcković J. Kirkpatrick Peter W. Battaglia 36 60 0 15 Jun 2021
Scalars are universal: Equivariant machine learning, structured like classical physics Soledad Villar D. Hogg Kate Storey-Fisher Weichi Yao Ben Blum-Smith PINN AI4CE 24 130 0 11 Jun 2021
Breaking the Limits of Message Passing Graph Neural Networks M. Balcilar Pierre Héroux Benoit Gaüzère Pascal Vasseur Sébastien Adam P. Honeine 13 121 0 08 Jun 2021
On the Equivalence Between Temporal and Static Graph Representations for Observational Predictions Jianfei Gao Bruno Ribeiro 27 11 0 12 Mar 2021
Size-Invariant Graph Representations for Graph Classification Extrapolations Beatrice Bevilacqua Yangze Zhou Bruno Ribeiro OOD 35 108 0 08 Mar 2021
Combinatorial optimization and reasoning with graph neural networks Quentin Cappart Didier Chételat Elias Boutros Khalil Andrea Lodi Christopher Morris Petar Velickovic AI4CE 32 346 0 18 Feb 2021
Graph Neural Networks: Taxonomy, Advances and Trends Yu Zhou Haixia Zheng Xin Huang Shufeng Hao Dengao Li Jumin Zhao AI4TS 25 115 0 16 Dec 2020
Design Space for Graph Neural Networks Jiaxuan You Rex Ying J. Leskovec GNN AI4CE 19 315 0 17 Nov 2020
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning Pan Li Yanbang Wang Hongwei Wang J. Leskovec GNN 20 12 0 31 Aug 2020
Expressive Power of Invariant and Equivariant Graph Neural Networks Waïss Azizian Marc Lelarge 22 111 0 28 Jun 2020
Hierarchical Inter-Message Passing for Learning on Molecular Graphs Matthias Fey Jan-Gin Yuen F. Weichert GNN 30 86 0 22 Jun 2020
Subgraph Neural Networks Emily Alsentzer S. G. Finlayson Michelle M. Li Marinka Zitnik GNN 18 134 0 18 Jun 2020
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Giorgos Bouritsas Fabrizio Frasca S. Zafeiriou M. Bronstein 46 423 0 16 Jun 2020