A Convergence Rate for Manifold Neural Networks

23 December 2022

Papers citing "A Convergence Rate for Manifold Neural Networks"

9 / 9 papers shown

Title
Convergence of Manifold Filter-Combine Networks David R. Johnson Joyce A. Chew Siddharth Viswanath E. Brouwer Deanna Needell Smita Krishnaswamy Michael Perlmutter 3DPC 40 0 0 18 Oct 2024
Generalization of Graph Neural Networks is Robust to Model Mismatch Zhiyang Wang J. Cerviño Alejandro Ribeiro 45 2 0 25 Aug 2024
Manifold Filter-Combine Networks Joyce A. Chew E. Brouwer Smita Krishnaswamy Deanna Needell Michael Perlmutter Michael Perlmutter GNN 28 0 0 08 Jul 2023
Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-offs Zhiyang Wang Luana Ruiz Alejandro Ribeiro GNN 41 7 0 29 May 2023
Convolutional Neural Networks on Manifolds: From Graphs and Back Zhiyang Wang Luana Ruiz Alejandro Ribeiro 3DPC GNN 40 14 0 01 Oct 2022
Robust Inference of Manifold Density and Geometry by Doubly Stochastic Scaling Boris Landa Xiuyuan Cheng 34 6 0 16 Sep 2022
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 176 1,111 0 27 Apr 2021
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation Xiuyuan Cheng Nan Wu 63 29 0 25 Jan 2021
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 259 3,240 0 24 Nov 2016