2 papers
cs.LG2025
Theoretical guarantees for the advantage of GNNs over NNs in generalizing bandlimited functions on Euclidean cubes
A. Martina Neuman, Rongrong Wang, Yuying Xie
Graph Neural Networks (GNNs) have emerged as formidable resources for processing graph-based information across diverse applications. While the expressive power of GNNs has traditi…
cs.LG2024
Transferability of Graph Neural Networks using Graphon and Sampling Theories
A. Martina Neuman, Jason J. Bramburger
Graph neural networks (GNNs) have become powerful tools for processing graph-based information in various domains. A desirable property of GNNs is transferability, where a trained…