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A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products
  and Graph Coarsening

A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening

13 June 2024
Guy Bar-Shalom
Yam Eitan
Fabrizio Frasca
Haggai Maron
ArXivPDFHTML

Papers citing "A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening"

4 / 4 papers shown
Title
Boosting the Cycle Counting Power of Graph Neural Networks with
  I$^2$-GNNs
Boosting the Cycle Counting Power of Graph Neural Networks with I2^22-GNNs
Yinan Huang
Xingang Peng
Jianzhu Ma
Muhan Zhang
76
46
0
22 Oct 2022
A Theoretical Comparison of Graph Neural Network Extensions
A Theoretical Comparison of Graph Neural Network Extensions
Pál András Papp
Roger Wattenhofer
95
45
0
30 Jan 2022
Reconstruction for Powerful Graph Representations
Reconstruction for Powerful Graph Representations
Leonardo Cotta
Christopher Morris
Bruno Ribeiro
AI4CE
122
78
0
01 Oct 2021
Benchmarking Graph Neural Networks
Benchmarking Graph Neural Networks
Vijay Prakash Dwivedi
Chaitanya K. Joshi
Anh Tuan Luu
T. Laurent
Yoshua Bengio
Xavier Bresson
186
913
0
02 Mar 2020
1