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On the approximation capability of GNNs in node
  classification/regression tasks
v1v2v3v4v5v6 (latest)

On the approximation capability of GNNs in node classification/regression tasks

16 June 2021
Giuseppe Alessio D’Inverno
Monica Bianchini
M. Sampoli
F. Scarselli
ArXiv (abs)PDFHTML

Papers citing "On the approximation capability of GNNs in node classification/regression tasks"

10 / 10 papers shown
Learning from one graph: transductive learning guarantees via the geometry of small random worlds
Learning from one graph: transductive learning guarantees via the geometry of small random worlds
Nils Detering
Luca Galimberti
Anastasis Kratsios
Giulia Livieri
A. M. Neuman
165
2
0
08 Sep 2025
Weisfeiler-Lehman meets Events: An Expressivity Analysis for Continuous-Time Dynamic Graph Neural Networks
Weisfeiler-Lehman meets Events: An Expressivity Analysis for Continuous-Time Dynamic Graph Neural Networks
Silvia Beddar-Wiesing
Alice Moallemy-Oureh
72
0
0
25 Aug 2025
A method for the systematic generation of graph XAI benchmarks via Weisfeiler-Leman coloring
A method for the systematic generation of graph XAI benchmarks via Weisfeiler-Leman coloring
Michele Fontanesi
Alessio Micheli
Marco Podda
Domenico Tortorella
304
0
0
18 May 2025
Physics-Informed GNN for non-linear constrained optimization: PINCO a
  solver for the AC-optimal power flow
Physics-Informed GNN for non-linear constrained optimization: PINCO a solver for the AC-optimal power flow
Anna Varbella
Damien Briens
B. Gjorgiev
Giuseppe Alessio DÍnverno
G. Sansavini
161
5
0
07 Oct 2024
Mesh-Informed Reduced Order Models for Aneurysm Rupture Risk Prediction
Mesh-Informed Reduced Order Models for Aneurysm Rupture Risk PredictionJournal of Computational and Applied Mathematics (JCAM), 2024
Giuseppe Alessio DÍnverno
Saeid Moradizadeh
Sajad Salavatidezfouli
Pasquale Claudio Africa
G. Rozza
AI4CE
339
5
0
04 Oct 2024
Computing Systemic Risk Measures with Graph Neural Networks
Computing Systemic Risk Measures with Graph Neural Networks
Lukas Gonon
Thilo Meyer-Brandis
Niklas Weber
301
1
0
30 Sep 2024
VC dimension of Graph Neural Networks with Pfaffian activation functions
VC dimension of Graph Neural Networks with Pfaffian activation functionsNeural Networks (NN), 2024
Giuseppe Alessio D’Inverno
Monica Bianchini
F. Scarselli
GNN
203
4
0
22 Jan 2024
Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach
Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach
Giovanni Luca Marchetti
Gabriele Cesa
Kumar Pratik
Arash Behboodi
337
2
0
14 Nov 2023
Generalization Limits of Graph Neural Networks in Identity Effects
  Learning
Generalization Limits of Graph Neural Networks in Identity Effects LearningNeural Networks (Neural Netw.), 2023
Giuseppe Alessio D’Inverno
Simone Brugiapaglia
Mirco Ravanelli
406
4
0
30 Jun 2023
Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of
  Graph Neural Networks for Attributed and Dynamic Graphs
Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic GraphsNeural Networks (NN), 2022
Silvia Beddar-Wiesing
Giuseppe Alessio D’Inverno
C. Graziani
Veronica Lachi
Alice Moallemy-Oureh
F. Scarselli
J. M. Thomas
261
13
0
08 Oct 2022
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