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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"

6 / 6 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
40
0
0
01 Jul 2024
Reconstruction for Powerful Graph Representations
Reconstruction for Powerful Graph Representations
Leonardo Cotta
Christopher Morris
Bruno Ribeiro
AI4CE
117
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
25
104
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
49
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
173
907
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
152
1,748
0
02 Mar 2017
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