VC dimension of Graph Neural Networks with Pfaffian activation functions
Fuente:
arXiv
Saved in:
| Main Authors: | D'Inverno, Giuseppe Alessio, Bianchini, Monica, Scarselli, Franco |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A topological description of loss surfaces based on Betti Numbers
by: Bucarelli, Maria Sofia, et al.
Published: (2024)
by: Bucarelli, Maria Sofia, et al.
Published: (2024)
On the approximation capability of GNNs in node classification/regression tasks
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2021)
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2021)
Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs
by: Beddar-Wiesing, Silvia, et al.
Published: (2022)
by: Beddar-Wiesing, Silvia, et al.
Published: (2022)
Comparison of Reservoir Computing topologies using the Recurrent Kernel approach
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2024)
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2024)
Surrogate models for diffusion on graphs via sparse polynomials
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2025)
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2025)
Physics-Informed GNN for non-linear constrained optimization: PINCO a solver for the AC-optimal power flow
by: Varbella, Anna, et al.
Published: (2024)
by: Varbella, Anna, et al.
Published: (2024)
Revisiting Deep Information Propagation: Fractal Frontier and Finite-size Effects
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2025)
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2025)
Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities
by: Longa, Antonio, et al.
Published: (2023)
by: Longa, Antonio, et al.
Published: (2023)
Product of Tensors and Description of Networks
by: Chiantini, Luca, et al.
Published: (2024)
by: Chiantini, Luca, et al.
Published: (2024)
On Task Vectors and Gradients
by: Zhou, Luca, et al.
Published: (2025)
by: Zhou, Luca, et al.
Published: (2025)
Mesh-Informed Reduced Order Models for Aneurysm Rupture Risk Prediction
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2024)
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2024)
Neural Learning of Fast Matrix Multiplication Algorithms: A StrassenNet Approach
by: Andreini, Paolo, et al.
Published: (2026)
by: Andreini, Paolo, et al.
Published: (2026)
Erzeugunsgrad, VC-Dimension and Neural Networks with rational activation function
by: Pardo, Luis Miguel, et al.
Published: (2025)
by: Pardo, Luis Miguel, et al.
Published: (2025)
An Empirical Evaluation of Rewiring Approaches in Graph Neural Networks
by: Micheli, Alessio, et al.
Published: (2023)
by: Micheli, Alessio, et al.
Published: (2023)
Early-Exit Graph Neural Networks
by: Di Francesco, Andrea Giuseppe, et al.
Published: (2025)
by: Di Francesco, Andrea Giuseppe, et al.
Published: (2025)
A note on the VC dimension of 1-dimensional GNNs
by: Daniëls, Noah, et al.
Published: (2024)
by: Daniëls, Noah, et al.
Published: (2024)
On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems
by: Gravina, Alessio, et al.
Published: (2024)
by: Gravina, Alessio, et al.
Published: (2024)
An innovative benefit‐of‐the‐doubt approach for health system effectiveness: a global case study on amenable mortality
by: Giovanna D'Inverno, et al.
Published: (2024)
by: Giovanna D'Inverno, et al.
Published: (2024)
Data-driven multi-agent modelling of calcium interactions in cell culture: PINN vs Regularized Least-squares
by: Poggi, Aurora, et al.
Published: (2025)
by: Poggi, Aurora, et al.
Published: (2025)
On the VC dimension of deep group convolutional neural networks
by: Sepliarskaia, Anna, et al.
Published: (2024)
by: Sepliarskaia, Anna, et al.
Published: (2024)
Algorithm Configuration for Structured Pfaffian Settings
by: Balcan, Maria-Florina, et al.
Published: (2024)
by: Balcan, Maria-Florina, et al.
Published: (2024)
L2XGNN: Learning to Explain Graph Neural Networks
by: Serra, Giuseppe, et al.
Published: (2022)
by: Serra, Giuseppe, et al.
Published: (2022)
Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
by: Gao, Nicholas, et al.
Published: (2024)
by: Gao, Nicholas, et al.
Published: (2024)
Contradiction Graphs Determine VC Dimension
by: Campbell, Jesse, et al.
Published: (2026)
by: Campbell, Jesse, et al.
Published: (2026)
Networks with Finite VC Dimension: Pro and Contra
by: Kurkova, Vera, et al.
Published: (2025)
by: Kurkova, Vera, et al.
Published: (2025)
Information propagation dynamics in Deep Graph Networks
by: Gravina, Alessio
Published: (2024)
by: Gravina, Alessio
Published: (2024)
Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State
by: Gao, Nicholas, et al.
Published: (2026)
by: Gao, Nicholas, et al.
Published: (2026)
On rough mereology and VC-dimension in treatment of decision prediction for open world decision systems
by: Polkowski, Lech T.
Published: (2024)
by: Polkowski, Lech T.
Published: (2024)
Graph Coordinates and Conventional Neural Networks -- An Alternative for Graph Neural Networks
by: Qin, Zheyi, et al.
Published: (2023)
by: Qin, Zheyi, et al.
Published: (2023)
MAGPrompt: Message-Adaptive Graph Prompt Tuning for Graph Neural Networks
by: Nguyen, Long D., et al.
Published: (2026)
by: Nguyen, Long D., et al.
Published: (2026)
Review of blockchain application with Graph Neural Networks, Graph Convolutional Networks and Convolutional Neural Networks
by: Ancelotti, Amy, et al.
Published: (2024)
by: Ancelotti, Amy, et al.
Published: (2024)
Neural networks with trainable matrix activation functions
by: Liu, Zhengqi, et al.
Published: (2021)
by: Liu, Zhengqi, et al.
Published: (2021)
From Graphs to Qubits: A Critical Review of Quantum Graph Neural Networks
by: Ceschini, Andrea, et al.
Published: (2024)
by: Ceschini, Andrea, et al.
Published: (2024)
Volatility in Certainty (VC): A Metric for Detecting Adversarial Perturbations During Inference in Neural Network Classifiers
by: Hemmati, Vahid, et al.
Published: (2025)
by: Hemmati, Vahid, et al.
Published: (2025)
Bounded Graph Clustering with Graph Neural Networks
by: Neocosmos, Kibidi, et al.
Published: (2025)
by: Neocosmos, Kibidi, et al.
Published: (2025)
Graph Kernel Neural Networks
by: Cosmo, Luca, et al.
Published: (2021)
by: Cosmo, Luca, et al.
Published: (2021)
Credal Graph Neural Networks
by: Tolloso, Matteo, et al.
Published: (2025)
by: Tolloso, Matteo, et al.
Published: (2025)
Memorization in Graph Neural Networks
by: Jamadandi, Adarsh, et al.
Published: (2025)
by: Jamadandi, Adarsh, et al.
Published: (2025)
Graph Variate Neural Networks
by: Roy, Om, et al.
Published: (2025)
by: Roy, Om, et al.
Published: (2025)
Graph Neural Networks on Graph Databases
by: Lopushanskyy, Dmytro, et al.
Published: (2024)
by: Lopushanskyy, Dmytro, et al.
Published: (2024)
Similar Items
-
A topological description of loss surfaces based on Betti Numbers
by: Bucarelli, Maria Sofia, et al.
Published: (2024) -
On the approximation capability of GNNs in node classification/regression tasks
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2021) -
Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs
by: Beddar-Wiesing, Silvia, et al.
Published: (2022) -
Comparison of Reservoir Computing topologies using the Recurrent Kernel approach
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2024) -
Surrogate models for diffusion on graphs via sparse polynomials
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2025)