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Optimality of Message-Passing Architectures for Sparse Graphs

Optimality of Message-Passing Architectures for Sparse Graphs

10 January 2025
Aseem Baranwal
K. Fountoulakis
Aukosh Jagannath
ArXivPDFHTML

Papers citing "Optimality of Message-Passing Architectures for Sparse Graphs"

17 / 17 papers shown
Title
Statistical physics analysis of graph neural networks: Approaching optimality in the contextual stochastic block model
O. Duranthon
L. Zdeborová
36
0
0
03 Mar 2025
Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral
  Methods and Graph Convolutional Networks
Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional Networks
Hai-Xiao Wang
Zhichao Wang
63
0
0
18 Dec 2024
The Intelligible and Effective Graph Neural Additive Networks
The Intelligible and Effective Graph Neural Additive Networks
Maya Bechler-Speicher
Amir Globerson
Ran Gilad-Bachrach
23
1
0
03 Jun 2024
Analysis of Corrected Graph Convolutions
Analysis of Corrected Graph Convolutions
Robert Wang
Aseem Baranwal
K. Fountoulakis
21
0
0
22 May 2024
Asymptotic generalization error of a single-layer graph convolutional
  network
Asymptotic generalization error of a single-layer graph convolutional network
O. Duranthon
L. Zdeborová
MLT
25
2
0
06 Feb 2024
TacticAI: an AI assistant for football tactics
TacticAI: an AI assistant for football tactics
Zhe Wang
Petar Velickovic
Daniel Hennes
Nenad Tomašev
Laurel Prince
...
Pol Moreno
N. Heess
Michael H. Bowling
Demis Hassabis
K. Tuyls
43
42
0
16 Oct 2023
Asynchronous Algorithmic Alignment with Cocycles
Asynchronous Algorithmic Alignment with Cocycles
Andrew Dudzik
Tamara von Glehn
Razvan Pascanu
Petar Velivcković
21
9
0
27 Jun 2023
Optimal Inference in Contextual Stochastic Block Models
Optimal Inference in Contextual Stochastic Block Models
O. Duranthon
L. Zdeborová
BDL
22
8
0
06 Jun 2023
Revisiting Robustness in Graph Machine Learning
Revisiting Robustness in Graph Machine Learning
Lukas Gosch
Daniel Sturm
Simon Geisler
Stephan Günnemann
AAML
OOD
53
12
0
01 May 2023
Homophily modulates double descent generalization in graph convolution
  networks
Homophily modulates double descent generalization in graph convolution networks
Chengzhi Shi
Liming Pan
Hong Hu
Ivan Dokmanić
21
9
0
26 Dec 2022
Message passing all the way up
Message passing all the way up
Petar Velickovic
103
63
0
22 Feb 2022
Generalization Analysis of Message Passing Neural Networks on Large
  Random Graphs
Generalization Analysis of Message Passing Neural Networks on Large Random Graphs
Sohir Maskey
Ron Levie
Yunseok Lee
Gitta Kutyniok
GNN
70
53
0
01 Feb 2022
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood
  Prediction
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction
Eli Chien
Wei-Cheng Chang
Cho-Jui Hsieh
Hsiang-Fu Yu
Jiong Zhang
O. Milenkovic
Inderjit S Dhillon
131
95
0
29 Oct 2021
Contextual Stochastic Block Models
Contextual Stochastic Block Models
Y. Deshpande
Andrea Montanari
Elchanan Mossel
S. Sen
98
131
0
23 Jul 2018
Representation Learning on Graphs with Jumping Knowledge Networks
Representation Learning on Graphs with Jumping Knowledge Networks
Keyulu Xu
Chengtao Li
Yonglong Tian
Tomohiro Sonobe
Ken-ichi Kawarabayashi
Stefanie Jegelka
GNN
217
1,726
0
09 Jun 2018
Interaction Networks for Learning about Objects, Relations and Physics
Interaction Networks for Learning about Objects, Relations and Physics
Peter W. Battaglia
Razvan Pascanu
Matthew Lai
Danilo Jimenez Rezende
Koray Kavukcuoglu
AI4CE
OCL
PINN
GNN
252
1,394
0
01 Dec 2016
Geometric deep learning on graphs and manifolds using mixture model CNNs
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
GNN
231
1,801
0
25 Nov 2016
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