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cs.LG2026
Consistent Geometric Deep Learning via Hilbert Bundles and Cellular Sheaves
Kartik Tandon, Julian Gould, Tanishq Bhatia +3
Modern deep learning architectures increasingly contend with sophisticated signals that are natively infinite-dimensional, such as time series, probability distributions, or operat…
cs.LG2025
A Manifold Perspective on the Statistical Generalization of Graph Neural Networks
Zhiyang Wang, Juan Cervino, Alejandro Ribeiro
Graph Neural Networks (GNNs) extend convolutional neural networks to operate on graphs. Despite their impressive performances in various graph learning tasks, the theoretical under…
cs.LG2024
Generalization of Graph Neural Networks is Robust to Model Mismatch
Zhiyang Wang, Juan Cervino, Alejandro Ribeiro
Graph neural networks (GNNs) have demonstrated their effectiveness in various tasks supported by their generalization capabilities. However, the current analysis of GNN generalizat…