3 papers
cs.LG2025
Multiscale Hodge Scattering Networks for Data Analysis
Naoki Saito, Stefan C. Schonsheck, Eugene Shvarts
We propose new scattering networks for signals measured on simplicial complexes, which we call \emph{Multiscale Hodge Scattering Networks} (MHSNs). Our construction builds on multi…
math.AT2025
Spherical Coordinates from Persistent Cohomology
Nikolas C. Schonsheck, Stefan C. Schonsheck
We describe a method to obtain spherical parameterizations of arbitrary data through the use of persistent cohomology and variational optimization. We begin by computing the second…
cs.LG2024
Semi-Supervised Manifold Learning with Complexity Decoupled Chart Autoencoders
Stefan C. Schonsheck, Scott Mahan, Timo Klock +2
Autoencoding is a popular method in representation learning. Conventional autoencoders employ symmetric encoding-decoding procedures and a simple Euclidean latent space to detect h…