Weisfeiler and Leman go Machine Learning: The Story so far

18 December 2021

Christopher Morris

Y. Lipman

Haggai Maron

Bastian Alexander Rieck

Nils M. Kriege

Papers citing "Weisfeiler and Leman go Machine Learning: The Story so far"

32 / 32 papers shown

Title
A Survey of Graph Transformers: Architectures, Theories and Applications Chaohao Yuan Kangfei Zhao Ercan Engin Kuruoglu Liang Wang Tingyang Xu Wenbing Huang Deli Zhao Hong Cheng Yu Rong 55 4 0 23 Feb 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
Improving Expressivity of Graph Neural Networks using Localization Anant Kumar Shrutimoy Das Shubhajit Roy Binita Maity Anirban Dasgupta 33 0 0 31 May 2023
A new perspective on building efficient and expressive 3D equivariant graph neural networks Weitao Du Yuanqi Du Limei Wang Dieqiao Feng Guifeng Wang Shuiwang Ji Carla P. Gomes Zhixin Ma AI4CE 27 33 0 07 Apr 2023
Graph Positional Encoding via Random Feature Propagation Moshe Eliasof Fabrizio Frasca Beatrice Bevilacqua Eran Treister Gal Chechik Haggai Maron 22 18 0 06 Mar 2023
Equivariant Polynomials for Graph Neural Networks Omri Puny Derek Lim B. Kiani Haggai Maron Y. Lipman 24 31 0 22 Feb 2023
On the Expressivity of Persistent Homology in Graph Learning Bastian Alexander Rieck Bastian Rieck 14 13 0 20 Feb 2023
Equivariant Architectures for Learning in Deep Weight Spaces Aviv Navon Aviv Shamsian Idan Achituve Ethan Fetaya Gal Chechik Haggai Maron 36 63 0 30 Jan 2023
GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation Han Huang Leilei Sun Bowen Du Yanjie Fu Weifeng Lv DiffM 29 42 0 04 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 33 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
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 23 14 0 24 Sep 2022
Gradual Weisfeiler-Leman: Slow and Steady Wins the Race Franka Bause Nils M. Kriege CLL 26 6 0 19 Sep 2022
Universally Expressive Communication in Multi-Agent Reinforcement Learning Matthew Morris Thomas D. Barrett Arnu Pretorius 24 4 0 14 Jun 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
Low Dimensional Invariant Embeddings for Universal Geometric Learning Nadav Dym S. Gortler 21 39 0 05 May 2022
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks Christopher Morris Gaurav Rattan Sandra Kiefer Siamak Ravanbakhsh 47 40 0 25 Mar 2022
A Simple and Universal Rotation Equivariant Point-cloud Network Ben Finkelshtein Chaim Baskin Haggai Maron Nadav Dym 3DPC 27 13 0 02 Mar 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 49 141 0 25 Feb 2022
A Theoretical Comparison of Graph Neural Network Extensions Pál András Papp Roger Wattenhofer 97 45 0 30 Jan 2022
Reconstruction for Powerful Graph Representations Leonardo Cotta Christopher Morris Bruno Ribeiro AI4CE 130 78 0 01 Oct 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 174 1,104 0 27 Apr 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 46 89 0 25 Feb 2021
Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing Jan Toenshoff Martin Ritzert Hinrikus Wolf Martin Grohe GNN 78 28 0 17 Feb 2021
The expressive power of kth-order invariant graph networks Floris Geerts 126 37 0 23 Jul 2020
Graph Homomorphism Convolution Hoang NT Takanori Maehara 95 40 0 03 May 2020
Universal Equivariant Multilayer Perceptrons Siamak Ravanbakhsh 98 48 0 07 Feb 2020
Convolutional Neural Network Architectures for Signals Supported on Graphs Fernando Gama A. Marques G. Leus Alejandro Ribeiro 132 285 0 01 May 2018
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 172 1,775 0 02 Mar 2017
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 222 14,099 0 02 Dec 2016
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 251 1,811 0 25 Nov 2016