107 citations · 207 across the 4 of their papers we have counts for
4 papers
Geomstats: A Python Package for Riemannian Geometry in Machine Learning
Nina Miolane, Alice Le Brigant, Johan Mathe +16
We introduce Geomstats, an open-source Python toolbox for computations and statistics on nonlinear manifolds, such as hyperbolic spaces, spaces of symmetric positive definite matri…
Adversarial Risk Bounds for Neural Networks through Sparsity based Compression
Emilio Rafael Balda, Arash Behboodi, Niklas Koep +1
Neural networks have been shown to be vulnerable against minor adversarial perturbations of their inputs, especially for high dimensional data under attacks. To comba…
The Restricted Isometry Property of Block Diagonal Matrices for Group-Sparse Signal Recovery
Niklas Koep, Arash Behboodi, Rudolf Mathar
Group-sparsity is a common low-complexity signal model with widespread application across various domains of science and engineering. The recovery of such signal ensembles from com…
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation
James Townsend, Niklas Koep, Sebastian Weichwald
Optimization on manifolds is a class of methods for optimization of an objective function, subject to constraints which are smooth, in the sense that the set of points which satisf…