196 citations · 359 across the 21 of their papers we have counts for
4 papers · 1 filter
Convolutional Filtering on Sampled Manifolds
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro
The increasing availability of geometric data has motivated the need for information processing over non-Euclidean domains modeled as manifolds. The building block for information…
A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs
Luana Ruiz, Ningyuan Huang, Soledad Villar
In this work we propose a random graph model that can produce graphs at different levels of sparsity. We analyze how sparsity affects the graph spectra, and thus the performance of…
Training Graph Neural Networks on Growing Stochastic Graphs
Juan Cervino, Luana Ruiz, Alejandro Ribeiro
Graph Neural Networks (GNNs) rely on graph convolutions to exploit meaningful patterns in networked data. Based on matrix multiplications, convolutions incur in high computational…
Convolutional Neural Networks on Manifolds: From Graphs and Back
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro
Geometric deep learning has gained much attention in recent years due to more available data acquired from non-Euclidean domains. Some examples include point clouds for 3D models a…