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Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond
  Message Passing

Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing

17 February 2021
Jan Toenshoff
Martin Ritzert
Hinrikus Wolf
Martin Grohe
    GNN
ArXivPDFHTML

Papers citing "Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing"

12 / 12 papers shown
Title
Revisiting Random Walks for Learning on Graphs
Revisiting Random Walks for Learning on Graphs
Jinwoo Kim
Olga Zaghen
Ayhan Suleymanzade
Youngmin Ryou
Seunghoon Hong
59
0
0
01 Jul 2024
Topology-Informed Graph Transformer
Topology-Informed Graph Transformer
Yuncheol Choi
Sun Woo Park
Minho Lee
Youngho Woo
30
3
0
03 Feb 2024
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
Federico Errica
Henrik Christiansen
Viktor Zaverkin
Takashi Maruyama
Mathias Niepert
Francesco Alesiani
54
7
0
27 Dec 2023
Diffusing Graph Attention
Diffusing Graph Attention
Daniel Glickman
Eran Yahav
GNN
47
3
0
01 Mar 2023
Recipe for a General, Powerful, Scalable Graph Transformer
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
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks
Christopher Morris
Gaurav Rattan
Sandra Kiefer
Siamak Ravanbakhsh
50
40
0
25 Mar 2022
Permute Me Softly: Learning Soft Permutations for Graph Representations
Permute Me Softly: Learning Soft Permutations for Graph Representations
Giannis Nikolentzos
George Dasoulas
Michalis Vazirgiannis
GNN
36
9
0
05 Oct 2021
Reconstruction for Powerful Graph Representations
Reconstruction for Powerful Graph Representations
Leonardo Cotta
Christopher Morris
Bruno Ribeiro
AI4CE
130
78
0
01 Oct 2021
Size-Invariant Graph Representations for Graph Classification
  Extrapolations
Size-Invariant Graph Representations for Graph Classification Extrapolations
Beatrice Bevilacqua
Yangze Zhou
Bruno Ribeiro
OOD
35
108
0
08 Mar 2021
Node2Seq: Towards Trainable Convolutions in Graph Neural Networks
Node2Seq: Towards Trainable Convolutions in Graph Neural Networks
Hao Yuan
Shuiwang Ji
GNN
82
7
0
06 Jan 2021
Benchmarking Graph Neural Networks
Benchmarking Graph Neural Networks
Vijay Prakash Dwivedi
Chaitanya K. Joshi
Anh Tuan Luu
T. Laurent
Yoshua Bengio
Xavier Bresson
189
916
0
02 Mar 2020
MoleculeNet: A Benchmark for Molecular Machine Learning
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
1,778
0
02 Mar 2017
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