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Weisfeiler-Lehman meets Gromov-Wasserstein

Weisfeiler-Lehman meets Gromov-Wasserstein

International Conference on Machine Learning (ICML), 2022
5 February 2022
Samantha Chen
Sunhyuk Lim
Facundo Mémoli
Qingsong Wang
Yusu Wang
    CoGe
ArXiv (abs)PDFHTMLGithub

Papers citing "Weisfeiler-Lehman meets Gromov-Wasserstein"

14 / 14 papers shown
What Expressivity Theory Misses: Message Passing Complexity for GNNs
What Expressivity Theory Misses: Message Passing Complexity for GNNs
Niklas Kemper
Tom Wollschlager
Stephan Günnemann
251
0
0
01 Sep 2025
Exploring Consistency in Graph Representations:from Graph Kernels to
  Graph Neural Networks
Exploring Consistency in Graph Representations:from Graph Kernels to Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2024
Xuyuan Liu
Yinghao Cai
Qihui Yang
Yujun Yan
260
2
0
31 Oct 2024
FSW-GNN: A Bi-Lipschitz WL-Equivalent Graph Neural Network
FSW-GNN: A Bi-Lipschitz WL-Equivalent Graph Neural Network
Yonatan Sverdlov
Yair Davidson
Nadav Dym
Tal Amir
352
8
0
10 Oct 2024
Graph Classification via Reference Distribution Learning: Theory and
  Practice
Graph Classification via Reference Distribution Learning: Theory and PracticeNeural Information Processing Systems (NeurIPS), 2024
Zixiao Wang
Jicong Fan
257
10
0
21 Aug 2024
Synchronous Diffusion for Unsupervised Smooth Non-Rigid 3D Shape
  Matching
Synchronous Diffusion for Unsupervised Smooth Non-Rigid 3D Shape Matching
Dongliang Cao
Zorah Laehner
Florian Bernard
DiffM
404
7
0
11 Jul 2024
On the Hölder Stability of Multiset and Graph Neural Networks
On the Hölder Stability of Multiset and Graph Neural Networks
Yair Davidson
Nadav Dym
636
5
0
11 Jun 2024
Bisimulation Metrics are Optimal Transport Distances, and Can be
  Computed Efficiently
Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
Sergio Calo
Anders Jonsson
Gergely Neu
Ludovic Schwartz
Javier Segovia
OT
383
5
0
06 Jun 2024
Resistance Distance and Linearized Optimal Transport on Graphs
Resistance Distance and Linearized Optimal Transport on Graphs
Sawyer Robertson
Zhengchao Wan
Alexander Cloninger
OT
454
3
0
23 Apr 2024
Comparing Graph Transformers via Positional Encodings
Comparing Graph Transformers via Positional Encodings
Mitchell Black
Qingsong Wang
Zhengchao Wan
A. Nayyeri
Yusu Wang
371
26
0
22 Feb 2024
Expressive Higher-Order Link Prediction through Hypergraph Symmetry
  Breaking
Expressive Higher-Order Link Prediction through Hypergraph Symmetry Breaking
Simon Zhang
Cheng Xin
Tamal K. Dey
255
3
0
17 Feb 2024
Future Directions in the Theory of Graph Machine Learning
Future Directions in the Theory of Graph Machine Learning
Christopher Morris
Fabrizio Frasca
Nadav Dym
Haggai Maron
.Ismail .Ilkan Ceylan
Ron Levie
Derek Lim
Michael M. Bronstein
Martin Grohe
Stefanie Jegelka
AI4CE
702
8
0
03 Feb 2024
Fine-grained Expressivity of Graph Neural Networks
Fine-grained Expressivity of Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2023
Jan Böker
Ron Levie
Ningyuan Huang
Soledad Villar
Christopher Morris
400
29
0
06 Jun 2023
Distances for Markov Chains, and Their Differentiation
Distances for Markov Chains, and Their DifferentiationInternational Conference on Algorithmic Learning Theory (ALT), 2023
Tristan Brugere
Qingsong Wang
Yusu Wang
OTOOD
264
5
0
16 Feb 2023
The Weisfeiler-Lehman Distance: Reinterpretation and Connection with
  GNNs
The Weisfeiler-Lehman Distance: Reinterpretation and Connection with GNNs
Samantha Chen
Sunhyuk Lim
Facundo Mémoli
Qingsong Wang
Yusu Wang
409
9
0
01 Feb 2023
1
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