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Future Directions in the Theory of Graph Machine Learning
3 February 2024
Christopher Morris
Fabrizio Frasca
Nadav Dym
Haggai Maron
.Ismail .Ilkan Ceylan
Ron Levie
Derek Lim
Michael M. Bronstein
Martin Grohe
Stefanie Jegelka
AI4CE
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Papers citing
"Future Directions in the Theory of Graph Machine Learning"
3 / 3 papers shown
Title
Graph Representational Learning: When Does More Expressivity Hurt Generalization?
Sohir Maskey
Raffaele Paolino
Fabian Jogl
Gitta Kutyniok
Johannes F. Lutzeyer
261
2
0
16 May 2025
The Expressive Power of Graph Neural Networks: A Survey
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023
Bingxue Zhang
Changjun Fan
Shixuan Liu
Kuihua Huang
Xiang Zhao
Jin-Yu Huang
Zhong Liu
408
41
0
16 Aug 2023
Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Large Random Graphs
Matthieu Cordonnier
Nicolas Keriven
Nicolas M Tremblay
Samuel Vaiter
GNN
464
12
0
21 Apr 2023
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